├── .github └── workflows │ └── python-package.yml ├── .gitignore ├── LICENSE ├── MANIFEST.in ├── README.md ├── cana ├── __init__.py ├── base.py ├── bns │ ├── __init__.py │ └── bns ├── boolean_network.py ├── boolean_node.py ├── canalization │ ├── __init__.py │ ├── boolean_canalization.py │ ├── cboolean_canalization.c │ └── cboolean_canalization.pyx ├── control │ ├── __init__.py │ ├── fvs.py │ ├── mds.py │ └── sc.py ├── cutils.c ├── cutils.pyx ├── datasets │ ├── __init__.py │ ├── bio.py │ ├── bns │ │ ├── arabidopsis.cnet │ │ ├── budding_yeast.cnet │ │ ├── drosophila4.cnet │ │ ├── fission_yeast.cnet │ │ ├── mammalian.cnet │ │ ├── tcr.cnet │ │ └── thelper.cnet │ ├── bools.py │ ├── breast_cancer.txt │ ├── cell_collective │ │ ├── Apoptosis Network.txt │ │ ├── Arabidopsis thaliana Cell Cycle.txt │ │ ├── Aurora Kinase A in Neuroblastoma.txt │ │ ├── B bronchiseptica and T retortaeformis coinfection.txt │ │ ├── B cell differentiation.txt │ │ ├── BT474 Breast Cell Line Long-term ErbB Network.txt │ │ ├── BT474 Breast Cell Line Short-term ErbB Network.txt │ │ ├── Bordetella bronchiseptica.txt │ │ ├── Bortezomib Responses in U266 Human Myeloma Cells.txt │ │ ├── Budding Yeast Cell Cycle 2009.txt │ │ ├── Budding Yeast Cell Cycle.txt │ │ ├── CD4 T cell signaling.txt │ │ ├── CD4+ T Cell Differentiation and Plasticity.txt │ │ ├── CD4+ T cell Differentiation.txt │ │ ├── Cardiac development.txt │ │ ├── Cell Cycle Transcription by Coupled CDK and Network Oscillators.txt │ │ ├── Cholesterol Regulatory Pathway.txt │ │ ├── Colitis-associated colon cancer.txt │ │ ├── Cortical Area Development.txt │ │ ├── Death Receptor Signaling.txt │ │ ├── Differentiation of T lymphocytes.txt │ │ ├── EGFR & ErbB Signaling.txt │ │ ├── FA BRCA pathway.txt │ │ ├── FGF pathway of Drosophila Signalling Pathways.txt │ │ ├── Fanconi anemia and checkpoint recovery.txt │ │ ├── Glucose Repression Signaling 2009.txt │ │ ├── Guard Cell Abscisic Acid Signaling.txt │ │ ├── HCC1954 Breast Cell Line Long-term ErbB Network.txt │ │ ├── HCC1954 Breast Cell Line Short-term ErbB Network.txt │ │ ├── HGF Signaling in Keratinocytes.txt │ │ ├── HH Pathway of Drosophila Signaling Pathways.txt │ │ ├── HIV-1 interactions with T Cell Signalling Pathway.txt │ │ ├── Human Gonadal Sex Determination.txt │ │ ├── IGVH mutations in chronic lymphocytic leukemia.txt │ │ ├── IL-1 Signaling.txt │ │ ├── IL-6 Signalling.txt │ │ ├── Influenza A Virus Replication Cycle.txt │ │ ├── Iron acquisition and oxidative stress response in aspergillus fumigatus.txt │ │ ├── Lac Operon.txt │ │ ├── Lymphoid and myeloid cell specification and transdifferentiation.txt │ │ ├── Lymphopoiesis Regulatory Network.txt │ │ ├── MAPK Cancer Cell Fate Network.txt │ │ ├── Mammalian Cell Cycle 2006.txt │ │ ├── Mammalian Cell Cycle.txt │ │ ├── Metabolic Interactions in the Gut Microbiome.txt │ │ ├── Neurotransmitter Signaling Pathway.txt │ │ ├── Oxidative Stress Pathway.txt │ │ ├── PC12 Cell Differentiation.txt │ │ ├── Predicting Variabilities in Cardiac Gene.txt │ │ ├── Pro-inflammatory Tumor Microenvironment in Acute Lymphoblastic Leukemia.txt │ │ ├── Processing of Spz Network from the Drosophila Signaling Pathway.txt │ │ ├── Regulation of the L-arabinose operon of Escherichia coli.txt │ │ ├── SKBR3 Breast Cell Line Long-term ErbB Network.txt │ │ ├── SKBR3 Breast Cell Line Short-term ErbB Network.txt │ │ ├── Senescence Associated Secretory Phenotype.txt │ │ ├── Septation Initiation Network.txt │ │ ├── Signal Transduction in Fibroblasts.txt │ │ ├── Signaling Pathway for Butanol Production in Clostridium beijerinckii NRRL B-598.txt │ │ ├── Signaling in Macrophage Activation.txt │ │ ├── Stomatal Opening Model.txt │ │ ├── T Cell Receptor Signaling.txt │ │ ├── T cell differentiation.txt │ │ ├── T-Cell Signaling 2006.txt │ │ ├── T-LGL Survival Network 2008.txt │ │ ├── T-LGL Survival Network 2011 Reduced Network.txt │ │ ├── T-LGL Survival Network 2011.txt │ │ ├── TOL Regulatory Network.txt │ │ ├── Toll Pathway of Drosophila Signaling Pathway.txt │ │ ├── Treatment of Castration-Resistant Prostate Cancer.txt │ │ ├── Trichostrongylus retortaeformis.txt │ │ ├── Tumour Cell Invasion and Migration.txt │ │ ├── VEGF Pathway of Drosophila Signaling Pathway.txt │ │ ├── Wg Pathway of Drosophila Signalling Pathways.txt │ │ └── Yeast Apoptosis.txt │ ├── drosophila_parasegment.txt │ ├── drosophila_single_cell.txt │ ├── leukemia.txt │ ├── marques-pita_rocha.txt │ ├── motifs.py │ ├── thaliana.txt │ └── yeast_cell_cycle.txt ├── drawing │ ├── __init__.py │ ├── canalizing_map.py │ └── schema_vis.py ├── random_boolean_network.py └── utils.py ├── docs ├── Makefile ├── make.bat └── source │ ├── appendix │ ├── index.rst │ └── smanicka_r_code.zip │ ├── bibliography.rst │ ├── conf.py │ ├── index.rst │ ├── reference │ ├── canalization │ │ └── index.rst │ ├── control │ │ └── index.rst │ ├── datasets │ │ ├── index.rst │ │ ├── networks.rst │ │ └── nodes.rst │ ├── ensemble.rst │ ├── index.rst │ ├── network.rst │ ├── node.rst │ └── utils.rst │ └── refs.bib ├── pyproject.toml ├── requirements.txt ├── setup.py ├── tests ├── __init__.py ├── helpers │ └── helper.py ├── test_boolean_canalization.py ├── test_boolean_network.py ├── test_boolean_node.py ├── test_effectiveness_measures.py └── test_two_symbol_symmetry.py └── tutorials ├── Canalization - BioModels - Look Up Table.ipynb ├── Canalization - BioModels - Schematas.ipynb ├── Canalization - BioModels.ipynb ├── Canalization - Marques-Pita.ipynb ├── Canalization - Node Schematas.ipynb ├── Control - BioModels - Driver Variables.ipynb ├── Control - State Transition Graph.ipynb ├── Control - Thaliana.ipynb ├── Dynamics Canalization Map - Breast Cancer.ipynb ├── Dynamics Canalization Map.ipynb ├── PNAS 2021 - Arabidopsis thaliana.ipynb └── PNAS 2021 - ER+ Breast Cancer.ipynb /.github/workflows/python-package.yml: -------------------------------------------------------------------------------- 1 | # This workflow will install Python dependencies, run tests and lint with a variety of Python versions 2 | # For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python 3 | 4 | name: Python package 5 | 6 | on: 7 | push: 8 | branches: [ "master" ] 9 | pull_request: 10 | branches: [ "master" ] 11 | 12 | jobs: 13 | build: 14 | 15 | runs-on: ubuntu-latest 16 | strategy: 17 | fail-fast: false 18 | matrix: 19 | python-version: ["3.10", "3.11", "3.12"] 20 | 21 | steps: 22 | - uses: actions/checkout@v3 23 | - name: Set up Python ${{ matrix.python-version }} 24 | uses: actions/setup-python@v3 25 | with: 26 | python-version: ${{ matrix.python-version }} 27 | - name: Install dependencies 28 | run: | 29 | python -m pip install --upgrade pip 30 | python -m pip install flake8 pytest 31 | if [ -f requirements.txt ]; then pip install -r requirements.txt; fi 32 | # - name: Lint with flake8 33 | # run: | 34 | # # stop the build if there are Python syntax errors or undefined names 35 | # flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics 36 | # # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide 37 | # flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics 38 | - name: Install cana 39 | run: | 40 | python -m pip install . 41 | - name: Clean up source 42 | run: | 43 | mkdir src/ 44 | mv cana/ src/ 45 | - name: Test with pytest 46 | run: | 47 | pytest 48 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Manualy defined 2 | experiments/ 3 | *bulk_test_log.csv 4 | .vscode 5 | 6 | # Byte-compiled / optimized / DLL files 7 | __pycache__/ 8 | *.py[cod] 9 | *$py.class 10 | 11 | # DS_Store 12 | .DS_Store 13 | 14 | # C extensions 15 | *.so 16 | 17 | # Distribution / packaging 18 | .Python 19 | env/ 20 | build/ 21 | develop-eggs/ 22 | dist/ 23 | downloads/ 24 | eggs/ 25 | .eggs/ 26 | lib/ 27 | lib64/ 28 | parts/ 29 | sdist/ 30 | var/ 31 | *.egg-info/ 32 | .installed.cfg 33 | *.egg 34 | 35 | # PyInstaller 36 | # Usually these files are written by a python script from a template 37 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 38 | *.manifest 39 | *.spec 40 | 41 | # Installer logs 42 | pip-log.txt 43 | pip-delete-this-directory.txt 44 | 45 | # Unit test / coverage reports 46 | htmlcov/ 47 | .tox/ 48 | .coverage 49 | .coverage.* 50 | .cache 51 | nosetests.xml 52 | coverage.xml 53 | *,cover 54 | .hypothesis/ 55 | 56 | # Translations 57 | *.mo 58 | *.pot 59 | 60 | # Django stuff: 61 | *.log 62 | local_settings.py 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # IPython Notebook 78 | .ipynb_checkpoints 79 | 80 | # pyenv 81 | .python-version 82 | 83 | # celery beat schedule file 84 | celerybeat-schedule 85 | 86 | # dotenv 87 | .env 88 | 89 | # virtualenv 90 | venv/ 91 | ENV/ 92 | 93 | # Spyder project settings 94 | .spyderproject 95 | 96 | # Rope project settings 97 | .ropeproject 98 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2017 Rion Brattig Correia 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /MANIFEST.in: -------------------------------------------------------------------------------- 1 | global-include *.pyx 2 | include cana/canalization/*.pyx 3 | include cana/datasets/*.txt 4 | include cana/datasets/bns/*.cnet 5 | include cana/datasets/cell_collective/*.txt -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | CANAlization: Control & Redundancy in Boolean Networks 2 | ======================================================= 3 | 4 | This package implements a series of methods used to study control, canalization and redundancy in Boolean Networks. 5 | 6 | Installation: 7 | ------------- 8 | 9 | ** Latest stable release ** 10 | 11 | - from PYPI 12 | ``` 13 | pip install cana 14 | ``` 15 | 16 | ** Latest development release on GitHub ** 17 | 18 | Pull and install the code directly from the github [project page](https://github.com/casci-lab/CANA). 19 | 20 | ``` 21 | pip install git+https://github.com/CASCI-lab/CANA 22 | ``` 23 | 24 | Please note that CANA uses Cython. For it to compile you may need to install the following: 25 | 26 | - `pip install Cython` 27 | 28 | Docs: 29 | ------- 30 | 31 | The full documentation can be found at: [casci-lab.github.io/CANA/](https://casci-lab.github.io/CANA/) 32 | 33 | 34 | Papers: 35 | --------- 36 | 37 | - A.J. Gates, R.B. Correia, X. Wang, L.M. Rocha [2021]. "[The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling](https://doi.org/10.1073/pnas.2022598118)". *Proceedings of the National Academy of Sciences (PNAS)*. 118(**12**). doi: 10.1073/pnas.20225981186 38 | 39 | - R.B. Correia, A.J. Gates, X. Wang, L.M. Rocha [2018]. "[CANA: A python package for quantifying control and canalization in Boolean Networks](https://www.informatics.indiana.edu/rocha/publications/FSB18.php)". *Frontiers in Physiology*. **9**: 1046. doi: 10.3389/fphys.2018.01046 40 | 41 | - A. Gates and L.M. Rocha. [2016] "[Control of complex networks requires both structure and dynamics.](http://www.informatics.indiana.edu/rocha/publications/NSR16.php)" *Scientific Reports* **6**, 24456. doi: 10.1038/srep24456. 42 | 43 | - A. Gates and L.M. Rocha [2014]. "[Structure and dynamics affect the controllability of complex systems: a Preliminary Study](http://www.informatics.indiana.edu/rocha/publications/alife14a.html)". *Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems*: 429-430, MIT Press. 44 | 45 | - M. Marques-Pita and L.M. Rocha [2013]. "[Canalization and control in automata networks: body segmentation in Drosophila Melanogaster](http://informatics.indiana.edu/rocha/publications/plos2012.html)". *PLoS ONE*, **8**(3): e55946. doi:10.1371/journal.pone.0055946. 46 | 47 | 48 | Credits: 49 | --------- 50 | 51 | ``CANA`` was originally written by Rion Brattig Correia and Alexander Gates, and has been developed 52 | with the help of many others. Thanks to everyone who has improved ``CANA`` by contributing code, bug reports (and fixes), documentation, and input on design, and features. 53 | 54 | 55 | **Original Authors** 56 | 57 | - [Rion Brattig Correia](http://alexandergates.net/), github: [rionbr](https://github.com/rionbr) 58 | - [Alexander Gates](https://alexandergates.net/), github: [ajgates42](https://github.com/ajgates42) 59 | 60 | 61 | **Contributors** 62 | 63 | Optionally, add your desired name and include a few relevant links. The order 64 | is an attempt at historical ordering. 65 | 66 | - [Xuan Wang](https://www.wangxuan.name), github: [xuan-w](https://github.com/xuan-w) 67 | - Thomas Parmer, github: [tjparmer](https://github.com/tjparmer) 68 | - Etienne Nzabarushimana 69 | - Luis M. Rocha 70 | 71 | 72 | Support 73 | ------- 74 | 75 | Those who have contributed to ``CANA`` have received support throughout the years from a variety of sources. We list them below. 76 | If you have provided support to ``CANA`` and a support acknowledgment does not appear below, please help us remedy the situation, and similarly, please let us know if you'd like something modified or corrected. 77 | 78 | **Research Groups** 79 | 80 | ``CANA`` was developed with support from the following: 81 | 82 | - [CASCI](https://homes.luddy.indiana.edu/rocha/casci.php), Indiana University, Bloomington, IN; PI: Luis M. Rocha 83 | - [CAPES Foundation](https://www.gov.br/capes/pt-br), Ministry of Education of Brazil, Brasília, Brazil; Rion B. Correia. 84 | 85 | 86 | Development 87 | ----------- 88 | Pull requests are welcome :) Please get in touch with one us beforehand: `rionbr(at)gmail(dot)com` or `ajgates42(at)gmail(dot)com`. 89 | 90 | ** TODOs** 91 | 92 | - Parallelize control methods; 93 | - Parallelize canalization methods; 94 | - Generating ensembles of dynamics from structural motifs; 95 | - Expand on easy-to-replicate tutorials; 96 | 97 | Tests 98 | ----- 99 | 100 | Run nosetests -v to perform tests and diagnoses on functions. 101 | 102 | 103 | Changelog 104 | --------- 105 | 106 | v0.1 107 | - Canalization methods ported to Cython 108 | 109 | v0.0.4 110 | - Pep8 and python3 111 | - Pinned controllability methods 112 | 113 | v0.0.3 114 | - Bugfixes 115 | 116 | v0.0.2 117 | - Networkx 2.1 compatibility 118 | - Inclusion of tutorials 119 | - Derrida curve 120 | 121 | v.0.0.1 122 | - Control (FVS, MDS, CSTG) methods. 123 | - Canalization methods. 124 | - Implementation ported to public package. 125 | -------------------------------------------------------------------------------- /cana/__init__.py: -------------------------------------------------------------------------------- 1 | __package__ = "cana" 2 | __title__ = "CANAlization: Control & Redundancy in Boolean Networks" 3 | __description__ = "This package implements a series of methods used to study control, canalization and redundancy in Boolean networks." 4 | 5 | __author__ = """\n""".join( 6 | [ 7 | "Rion Brattig Correia ", 8 | "Alex Gates ", 9 | "Xuan Wang ", 10 | "Thomas Parmer ", 11 | "Etienne Nzabarushimana ", 12 | "Luis M. Rocha ", 13 | ] 14 | ) 15 | 16 | __copyright__ = "2021, Correia, R. B., Gates, A., Rocha, L. M." 17 | 18 | __version__ = "1.0.0" 19 | __release__ = "1.0.0" 20 | # 21 | __all__ = ["boolean_network", "boolean_node"] 22 | -------------------------------------------------------------------------------- /cana/base.py: -------------------------------------------------------------------------------- 1 | import functools 2 | import warnings 3 | 4 | 5 | def deprecated(func): 6 | """This is a decorator which can be used to mark functions as deprecated. 7 | It will result in a warning being emitted when the function is used. 8 | """ 9 | 10 | @functools.wraps(func) 11 | def new_func(*args, **kwargs): 12 | warnings.warn_explicit( 13 | "You've called a deprecated function. Maybe this function needs updating to the new package. {}".format( 14 | func.__name__ 15 | ), 16 | category=DeprecationWarning, 17 | filename=func.func_code.co_filename, 18 | lineno=func.func_code.co_firstlineno + 1, 19 | ) 20 | return func(*args, **kwargs) 21 | 22 | return new_func 23 | -------------------------------------------------------------------------------- /cana/bns/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | BNS Attractors Interface 4 | ========================== 5 | 6 | This module interfaces CANA with the [B]oolean [N]etworks with [S]ynchronous update (BNS) :cite:`Dubrova:2011` to compute attractors. 7 | 8 | BNS is a software tool for computing attractors in Boolean Networks with Synchronous update. 9 | Synchronous Boolean networks are used for the modeling of genetic regulatory networks. 10 | 11 | BNS implements the algorithm presented in which is based on a SAT-based bounded model checking. 12 | BNS uses much less space compared to BooleNet or other BDD-based approaches for computing attractors. 13 | It can handle several orders of magnitude larger networks. 14 | 15 | 16 | 17 | .. Note:: 18 | 19 | You must have ``bns`` compiled for you system. Alternatively, you can download the binary from the `bns website `_ directly. 20 | Last updated: March 2017. 21 | 22 | """ 23 | # Copyright (C) 2017 by 24 | # Rion Brattig Correia 25 | # Alex Gates 26 | # All rights reserved. 27 | # MIT license. 28 | import os 29 | import subprocess 30 | import tempfile 31 | 32 | from cana.utils import binstate_to_statenum 33 | 34 | _path = os.path.dirname(os.path.realpath(__file__)) 35 | """ Make sure we know what the current directory is """ 36 | 37 | 38 | def attractors(cnet, bnspath=_path, cleanup=True): 39 | """Makes a subprocess call to `bns` supplying a temporary file with the boolean logic. 40 | 41 | Args: 42 | cnet (file,string) : A .cnet formated string or file. 43 | bnspath (string) : The path to the bns binary. 44 | cleanup (bool) : If cnet is a string, this function creates a temporary file. This forces the removal of this temp file. 45 | 46 | Returns: 47 | list : the list of attractors 48 | """ 49 | 50 | # If is file, open the file 51 | if os.path.isfile(cnet): 52 | file = cnet 53 | 54 | # If string, Creates a Temporary File to be supplied to BNS 55 | elif isinstance(cnet, str): 56 | tmp = tempfile.NamedTemporaryFile(delete=cleanup) 57 | with open(tmp.name, "w") as openfile: 58 | openfile.write(cnet) 59 | tmp.file.close() 60 | file = tmp.name 61 | else: 62 | raise TypeError( 63 | "The cnet input should be either a file to a .cnet file or a string containing the .cnet content" 64 | ) 65 | 66 | cmd = [os.path.join(bnspath, "bns"), file] 67 | attractors = list() 68 | 69 | try: 70 | p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) 71 | 72 | current_attractor = [] 73 | for _, line in enumerate(p.stdout): 74 | # Strip line 75 | cleanline = line.decode("ascii").strip().replace("\n", "") 76 | 77 | if "Attractor" in cleanline: 78 | attractors.append(current_attractor) 79 | current_attractor = [] 80 | elif "Node" in cleanline and "assumed to be constant" in cleanline: 81 | pass 82 | elif "Total" in cleanline: 83 | pass 84 | elif "Start searching for all atractors." in cleanline: 85 | pass 86 | elif "Depth" in cleanline: 87 | pass 88 | elif "average" in cleanline: 89 | pass 90 | elif len(cleanline) > 0: 91 | current_attractor.append(binstate_to_statenum(cleanline)) 92 | 93 | except OSError: 94 | print( 95 | "'BNS' could not be found! You must have it compiled or download the binary for your system from the 'bns' website (https://people.kth.se/~dubrova/bns.html)." 96 | ) 97 | 98 | return attractors 99 | -------------------------------------------------------------------------------- /cana/bns/bns: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/cana/bns/bns -------------------------------------------------------------------------------- /cana/canalization/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/cana/canalization/__init__.py -------------------------------------------------------------------------------- /cana/control/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/cana/control/__init__.py -------------------------------------------------------------------------------- /cana/control/mds.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Minimum Dominating Set 4 | ======================= 5 | 6 | 7 | """ 8 | # Copyright (C) 2021 by 9 | # Alex Gates 10 | # Rion Brattig Correia 11 | # All rights reserved. 12 | # MIT license. 13 | import itertools 14 | 15 | 16 | # 17 | # Minimum Dominating Set 18 | # 19 | def mds(directed_graph, max_search=5, keep_self_loops=True): 20 | """The minimum dominating set method. 21 | 22 | Args: 23 | directed_graph (networkx.DiGraph) : The structural graph. 24 | max_search (int) : Maximum search of additional variables. Defaults to 5. 25 | keep_self_loops (bool) : If self-loops are used in the computation. 26 | Returns: 27 | (list) : A list of sets with the driver nodes. 28 | """ 29 | N = len(directed_graph) 30 | root_var = _root_variables(directed_graph, keep_self_loops=keep_self_loops) 31 | 32 | if len(_get_dominated_set(directed_graph, root_var)) == N: 33 | return [root_var] 34 | else: 35 | MDS_sets = [] 36 | nonroot_variables = set(directed_graph.nodes()) - set(root_var) 37 | for num_additional_var in range(1, max_search): 38 | for an_combo in itertools.combinations( 39 | nonroot_variables, num_additional_var 40 | ): 41 | possible_dvs = root_var.union(an_combo) 42 | if len(_get_dominated_set(directed_graph, possible_dvs)) == N: 43 | MDS_sets.append(possible_dvs) 44 | if len(MDS_sets) > 0: 45 | break 46 | return MDS_sets 47 | 48 | 49 | def _get_dominated_set(directed_graph, dominatingset): 50 | """ 51 | TODO 52 | """ 53 | dominatedset = set(dominatingset) 54 | for dn in dominatingset: 55 | dominatedset.update(directed_graph.neighbors(dn)) 56 | return dominatedset 57 | 58 | 59 | def _root_variables(directed_graph, keep_self_loops=True): 60 | """ """ 61 | return set( 62 | [ 63 | n 64 | for n in directed_graph.nodes() 65 | if (directed_graph.in_degree(n) == 0) 66 | or ((not keep_self_loops) and (directed_graph.neighbors(n) == [n])) 67 | ] 68 | ) 69 | -------------------------------------------------------------------------------- /cana/datasets/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/cana/datasets/__init__.py -------------------------------------------------------------------------------- /cana/datasets/bns/arabidopsis.cnet: -------------------------------------------------------------------------------- 1 | # Boolean network model of the control of flower morphogenesis in Arabidobis thaliana 2 | # "From Genes to Flower Patterns and Evolution: Dynamic Models of Gene Regulatory Networks" 3 | # A. Chaos, M. Aldana, C. Espinosa-Soto, B. G. P. de Leon, A. G. Arroyo, E. R. Alvarez-Buylla, 4 | # Journal of Plant Growth Regulation, vol. 25, n. 4, 2006, pp. 278-289 5 | # The functions associated to nodes are minimized 6 | 7 | #total number of nodes 8 | .v 15 9 | 10 | # labels of nodes and name of corresponding genes 11 | # 1 = AP3 12 | # 2 = UFO 13 | # 3 = FUL 14 | # 4 = FT 15 | # 5 = AP1 16 | # 6 = EMF1 17 | # 7 = LFY 18 | # 8 = AP2 19 | # 9 = WUS 20 | # 10 = AG 21 | # 11 = LUG 22 | # 12 = CLF 23 | # 13 = TFL1 24 | # 14 = PI 25 | # 15 = SEP 26 | 27 | # As a result of simulation, we get the following 10 single-point attractors: 28 | # 101100110111011 29 | # 110110110011011 30 | # 100110110011011 31 | # 111100110111011 32 | # 010001000011100 33 | # 010001001011100 34 | # 001100110111011 35 | # 000110110011001 36 | # 000001000011100 37 | # 000001001011100 38 | 39 | # 1 = AP3 40 | .n 1 7 5 7 10 14 15 1 2 41 | --1111- 1 42 | 1--111- 1 43 | -1----1 1 44 | -0-0--- 0 45 | -0--0-- 0 46 | -0---0- 0 47 | ---0--0 0 48 | ----0-0 0 49 | -----00 0 50 | 000---- 0 51 | 0-0---0 0 52 | 53 | # 2 = UFO 54 | .n 2 1 2 55 | 1 1 56 | 0 0 57 | 58 | # 3 = FUL 59 | .n 3 2 5 13 60 | 00 1 61 | 1- 0 62 | -1 0 63 | 64 | # 4 = FT 65 | .n 4 1 6 66 | 0 1 67 | 1 0 68 | 69 | # 5 = AP1 70 | .n 5 4 4 7 10 13 71 | --00 1 72 | -10- 1 73 | 1-0- 1 74 | 00-1 0 75 | --1- 0 76 | 77 | # 6 = EMF1 78 | .n 6 1 7 79 | 0 1 80 | 1 0 81 | 82 | # 7 = LFY 83 | .n 7 4 3 5 6 13 84 | ---0 1 85 | --0- 1 86 | --11 0 87 | 88 | # 8 = AP2 89 | .n 8 1 13 90 | 0 1 91 | 1 0 92 | 93 | # 9 = WUS 94 | .n 9 3 9 10 15 95 | 1-0 1 96 | 10- 1 97 | -11 0 98 | 0-- 0 99 | 100 | # 10 = AG 101 | .n 10 9 5 7 8 9 10 11 12 13 15 102 | -1--1---1 1 103 | --0----0- 1 104 | -1----0-- 1 105 | -1---0--- 1 106 | -1-1----- 1 107 | 01------- 1 108 | -10------ 1 109 | -01------ 0 110 | -0-----1- 0 111 | 1-10011-- 0 112 | 1-10-11-0 0 113 | 114 | # 11 = LUG 115 | .n 11 0 116 | 1 117 | 118 | # 12 = CLF 119 | .n 12 0 120 | 1 121 | 122 | # 13 = TFL1 123 | .n 13 4 5 6 7 8 124 | 010- 1 125 | 1--- 0 126 | -0-- 0 127 | --1- 0 128 | 129 | # 14 = PI 130 | .n 14 6 5 7 10 14 15 1 131 | 1--111 1 132 | --1111 1 133 | -11--- 1 134 | -1---1 1 135 | -0-0-- 0 136 | -0--0- 0 137 | -0---0 0 138 | --0--0 0 139 | 000--- 0 140 | 141 | # 15 = SEP 142 | .n 15 1 7 143 | 1 1 144 | 0 0 145 | 146 | 147 | 148 | 149 | 150 | -------------------------------------------------------------------------------- /cana/datasets/bns/budding_yeast.cnet: -------------------------------------------------------------------------------- 1 | # Boolean network model of the control of the budding yeast cell cycle regulation from 2 | # "The yeast cell-cycle network is robustly designed", 3 | # Fangting Li, Tao Long, Ying Lu, Qi Ouyang, Chao Tang, 4 | # PNAS April 6, 2004, vol. 101 no. 14 4781-4786. 5 | 6 | #total number of nodes 7 | .v 12 8 | 9 | # labels of nodes and names of corresponding components 10 | # 1 = Cell size 11 | # 2 = Cln3 12 | # 3 = SBF 13 | # 4 = MBF 14 | # 5 = Cln1,2 15 | # 6 = Sic1 16 | # 7 = Cln5,6 17 | # 8 = Cdh1 18 | # 9 = Clb1,2 19 | # 10 = Mcm1/SFF 20 | # 11 = Cdc20&Cdc14 21 | # 12 = Swi5 22 | 23 | # As a result of simulation, we get the following 7 attractors of length 1: 24 | # 001010000000 25 | # 000101000000 26 | # 000101010000 27 | # 000000000000 28 | # 000001000000 29 | # 000000010000 30 | # 000001010000 31 | 32 | # 1 = Cell size 33 | .n 1 0 34 | 35 | # 2 = Cln3 36 | .n 2 1 1 37 | 1 1 38 | 0 0 39 | 40 | # 3 = SBF 41 | .n 3 3 2 3 9 42 | -10 1 43 | 11- 1 44 | 1-0 1 45 | 00- 0 46 | 0-1 0 47 | -01 0 48 | 49 | # 4 = MBF 50 | .n 4 3 2 4 9 51 | -10 1 52 | 11- 1 53 | 1-0 1 54 | 00- 0 55 | 0-1 0 56 | -01 0 57 | 58 | # 5 = Cln1,2 59 | .n 5 1 3 60 | 1 1 61 | 0 0 62 | 63 | # 6 = Sic1 64 | .n 6 6 5 6 7 9 11 12 65 | 0100-- 1 66 | -1001- 1 67 | 01-01- 1 68 | 010-1- 1 69 | -100-1 1 70 | 01-0-1 1 71 | 010--1 1 72 | -1-011 1 73 | -10-11 1 74 | 01--11 1 75 | 0-00-1 1 76 | --0011 1 77 | 0--011 1 78 | 0-0-11 1 79 | 0-001- 1 80 | 101--- 0 81 | 10-1-- 0 82 | 1-11-- 0 83 | -011-- 0 84 | 10--0- 0 85 | 1-1-0- 0 86 | -01-0- 0 87 | 1--10- 0 88 | -0-10- 0 89 | --110- 0 90 | 10---0 0 91 | 1-1--0 0 92 | -01--0 0 93 | 1--1-0 0 94 | -0-1-0 0 95 | --11-0 0 96 | 1---00 0 97 | -0--00 0 98 | --1-00 0 99 | ---100 0 100 | 101 | # 7 = Cln5,6 102 | .n 7 4 4 6 7 11 103 | -010 1 104 | 1-10 1 105 | 101- 1 106 | 10-0 1 107 | 01-- 0 108 | 0-0- 0 109 | -10- 0 110 | 0--1 0 111 | -1-1 0 112 | --01 0 113 | 114 | # 8 = Cdh1 115 | .n 8 5 5 7 8 9 11 116 | 0010- 1 117 | -0101 1 118 | 0-101 1 119 | 001-1 1 120 | 00-01 1 121 | 11--- 0 122 | 1-0-- 0 123 | -10-- 0 124 | 1--1- 0 125 | -1-1- 0 126 | --01- 0 127 | 1---0 0 128 | -1--0 0 129 | --0-0 0 130 | ---10 0 131 | 132 | # 9 = Clb1,2 133 | .n 9 6 6 7 8 9 10 11 134 | 0101-- 1 135 | 0-011- 1 136 | -1011- 1 137 | 01-11- 1 138 | 0-01-0 1 139 | -101-0 1 140 | 01-1-0 1 141 | --0110 1 142 | 0--110 1 143 | -1-110 1 144 | 010--0 1 145 | 0-0-10 1 146 | -10-10 1 147 | 01--10 1 148 | 010-1- 1 149 | 101--- 0 150 | 10-0-- 0 151 | 1-10-- 0 152 | -010-- 0 153 | 10--0- 0 154 | 1-1-0- 0 155 | -01-0- 0 156 | 1--00- 0 157 | -0-00- 0 158 | --100- 0 159 | 10---1 0 160 | 1-1--1 0 161 | -01--1 0 162 | 1--0-1 0 163 | -0-0-1 0 164 | --10-1 0 165 | 1---01 0 166 | -0--01 0 167 | --1-01 0 168 | ---001 0 169 | 170 | # 10 = Mcm1/SFF 171 | .n 10 2 7 9 172 | -1 1 173 | 1- 1 174 | 00 0 175 | 176 | # 11 = Cdc20&Cdc14 177 | .n 11 2 9 10 178 | -1 1 179 | 1- 1 180 | 00 0 181 | 182 | # 12 = Swi5 183 | .n 12 4 9 10 11 12 184 | 0-1- 1 185 | -11- 1 186 | 01-- 1 187 | 10-- 0 188 | 1-0- 0 189 | -00- 0 190 | 191 | 192 | 193 | 194 | 195 | 196 | -------------------------------------------------------------------------------- /cana/datasets/bns/fission_yeast.cnet: -------------------------------------------------------------------------------- 1 | # Boolean network model of the control of the fission yeast cell cycle regulation from 2 | # "Boolean Network Model Predicts Cell Cycle Sequence of Fission Yeast", 3 | # M. I. Davidich, S. Bornholdt, PLoS ONE. 2008 Feb 27, 3(2):e1672. 4 | 5 | #total number of nodes 6 | .v 10 7 | 8 | # labels of nodes and names of corresponding components 9 | # 1 = Start 10 | # 2 = SK 11 | # 3 = Ste9 12 | # 4 = Cdc2/Cdc13 13 | # 5 = Rum1 14 | # 6 = PP 15 | # 7 = Cdc25 16 | # 8 = Slp1 17 | # 9 = Wee1/Mik1 18 | # 10 = Cdc2/Cdc13* 19 | # 20 | # The threshold is -1 for the node Cdc2/Cdc13 and 1 for Cdc2/Cdc13* 21 | # for all other nodes the threshold is 0 22 | 23 | # As a result of simulation, we get the following 13 attractors of length 1: 24 | # 0010100010 25 | # 0010001000 26 | # 0010101010 27 | # 0010100000 28 | # 0010000000 29 | # 0000100000 30 | # 0010101000 31 | # 0000100010 32 | # 0001001000 33 | # 0000101000 34 | # 0010000010 35 | # 0010001010 36 | # 0000101010 37 | 38 | # 1 = Start 39 | .n 1 0 40 | 41 | # 2 = SK 42 | .n 2 1 1 43 | 1 1 44 | 0 0 45 | 46 | # 3 = Ste9 47 | .n 3 5 2 3 4 6 10 48 | 010-0 1 49 | -1010 1 50 | 01-10 1 51 | 0101- 1 52 | 0-010 1 53 | 10--- 0 54 | 1-1-- 0 55 | -01-- 0 56 | 1--0- 0 57 | -0-0- 0 58 | --10- 0 59 | 1---1 0 60 | -0--1 0 61 | --1-1 0 62 | ---01 0 63 | 64 | # 4 = Cdc2/Cdc13 65 | .n 4 4 3 4 5 8 66 | -100 1 67 | 01-0 1 68 | 010- 1 69 | 0-00 1 70 | 10-- 0 71 | 1-1- 0 72 | -01- 0 73 | 1--1 0 74 | -0-1 0 75 | --11 0 76 | 77 | # 5 = Rum1 78 | .n 5 5 2 4 5 6 10 79 | -0111 1 80 | 001-0 1 81 | 0-110 1 82 | 00-10 1 83 | -10-- 0 84 | -1-0- 0 85 | --00- 0 86 | 1---0 0 87 | -1--1 0 88 | --0-1 0 89 | ---01 0 90 | 91 | # 6 = PP 92 | .n 6 1 8 93 | 1 1 94 | 0 0 95 | 96 | # 7 = Cdc25 97 | .n 7 3 4 6 7 98 | -01 1 99 | 1-1 1 100 | 10- 1 101 | 01- 0 102 | 0-0 0 103 | -10 0 104 | 105 | # 8 = Slp1 106 | .n 8 1 10 107 | 1 1 108 | 0 0 109 | 110 | # 9 = Wee1/Mik1 111 | .n 9 3 4 6 9 112 | 0-1 1 113 | -11 1 114 | 01- 1 115 | 10- 0 116 | 1-0 0 117 | -00 0 118 | 119 | # 10 = Cdc2/Cdc13* 120 | .n 10 6 3 5 7 8 9 10 121 | 001001 1 122 | 1----- 0 123 | -1---- 0 124 | --0--- 0 125 | ---1-- 0 126 | ----1- 0 127 | -----0 0 128 | 129 | 130 | -------------------------------------------------------------------------------- /cana/datasets/bns/mammalian.cnet: -------------------------------------------------------------------------------- 1 | # Boolean network model of the control of the mammalian cell cycle from 2 | # "Dynamical Analysis of a Generic Boolean Model for the Control of the 3 | # Mammalian Cell Cycle", A. Faure, A. Naldi, C. Chaouiya, D. Thieffry, 4 | # Bioinformatics, 2006, vol. 22, no. 14, pp. e124-e131. 5 | 6 | #total number of nodes 7 | .v 10 8 | 9 | # labels of nodes and names of corresponding components 10 | # 1 = CycD 11 | # 2 = CycE 12 | # 3 = Rb 13 | # 4 = E2F 14 | # 5 = CycA 15 | # 6 = p27 16 | # 7 = Cdc20 17 | # 8 = UbcH10 18 | # 9 = Cdh1 19 | # 10 = CycB 20 | 21 | # As a result of simulation, we get the following 2 attractors: 22 | # 23 | # 1101100010 24 | # 1100100000 25 | # 1000100101 26 | # 1000101101 27 | # 1000001110 28 | # 1001000110 29 | # 1101000010 30 | # Attractor 1 is of length 7 31 | # 32 | # 0010010010 33 | # Attractor 2 is of length 1 34 | 35 | # 1 = CycD 36 | .n 1 1 1 37 | 1 1 38 | 0 0 39 | 40 | # 2 = CycE 41 | .n 2 2 3 4 42 | 01 1 43 | 1- 0 44 | -0 0 45 | 46 | # 3 = Rb 47 | .n 3 5 1 2 5 6 10 48 | 000-0 1 49 | 0--10 1 50 | -1-0- 0 51 | --10- 0 52 | 1---- 0 53 | ----1 0 54 | 55 | # 4 = E2F 56 | .n 4 4 3 5 6 10 57 | 0-10 1 58 | 00-0 1 59 | -10- 0 60 | 1--- 0 61 | ---1 0 62 | 63 | # 5 = CycA 64 | .n 5 6 3 4 5 7 8 9 65 | 0-10-0 1 66 | 01-0-0 1 67 | 0-100- 1 68 | 01-00- 1 69 | -00--- 0 70 | ----11 0 71 | 1----- 0 72 | ---1-- 0 73 | 74 | # 6 = p27 75 | .n 6 5 1 2 5 6 10 76 | 0-010 1 77 | 00-10 1 78 | 000-0 1 79 | -11-- 0 80 | -1-0- 0 81 | --10- 0 82 | 1---- 0 83 | ----1 0 84 | 85 | # 7 = Cdc20 86 | .n 7 1 10 87 | 1 1 88 | 0 0 89 | 90 | # 8 = UbcH10 91 | .n 8 5 5 7 8 9 10 92 | --1-1 1 93 | -11-- 1 94 | 1-1-- 1 95 | ---0- 1 96 | --01- 0 97 | 00-10 0 98 | 99 | # 9 = Cdh1 100 | .n 9 4 5 6 7 10 101 | -1-0 1 102 | 0--0 1 103 | --1- 1 104 | --01 0 105 | 100- 0 106 | 107 | # 10 = CycB 108 | .n 10 2 7 9 109 | 00 1 110 | 1- 0 111 | -1 0 112 | -------------------------------------------------------------------------------- /cana/datasets/bns/tcr.cnet: -------------------------------------------------------------------------------- 1 | # Boolean network model of the T-cell receptor signalling pathway from 2 | # "A methodology for the structural and functional analysis of signaling and 3 | # regulatory networks", S. Klamt, J. Saez-Rodriguez, J. A. Lindquist, L. Simeoni, E. D. Gilles, 4 | # JBMC Bioinformatics 7: 56, 2006. 5 | 6 | # total number of nodes 7 | .v 40 8 | 9 | # labels of nodes and names of corresponding components 10 | # 1 = CD45 11 | # 2 = CD8 12 | # 3 = TCRlig 13 | # 4 = TCbind 14 | # 5 = PAGCsk 15 | # 6 = LCK 16 | # 7 = Fyn 17 | # 8 = Rlk 18 | # 9 = TCRphos 19 | # 10 = ZAP70 20 | # 11 = cCbl 21 | # 12 = Itk 22 | # 13 = LAT 23 | # 14 = Gads 24 | # 15 = Slp76 25 | # 16 = PLCg_b 26 | # 17 = Grb2Sos 27 | # 18 = DAG 28 | # 19 = PLCg_a 29 | # 20 = Ras 30 | # 21 = RasGRP1 31 | # 22 = PKCth 32 | # 23 = IP3 33 | # 24 = Raf 34 | # 25 = MEK 35 | # 26 = Ca 36 | # 27 = ERK 37 | # 28 = SEK 38 | # 29 = IKK 39 | # 30 = Calcin 40 | # 31 = Rsk 41 | # 32 = Fos 42 | # 33 = JNK 43 | # 34 = IkB 44 | # 35 = CREB 45 | # 36 = Jun 46 | # 37 = CRE 47 | # 38 = AP1 48 | # 39 = NFkB 49 | # 40 = NFAT 50 | 51 | # As a result of simulation, we get the following 9 attractors: 52 | # 53 | # 1111101010101000000000000000001101000000 54 | # 1110101010000101100000000000000001100000 55 | # 1111100010000010000100000000000001001000 56 | # 1111001000000000000000010000000001000000 57 | # 1111111010000000000000001000000001000000 58 | # 1111101111000000000000000010000001000000 59 | # Attractor 1 is of length 6 60 | # 61 | # 1111101010000000000000000000000001000000 62 | # Attractor 2 is of length 1 63 | # 64 | # 1100100000000000000000000000000001000000 65 | # Attractor 3 is of length 1 66 | # 67 | # 1011101010000000000000000000000001000000 68 | # Attractor 4 is of length 1 69 | # 70 | # 0000100000000000000000000000000001000000 71 | # Attractor 5 is of length 1 72 | # 73 | # 0011000000000000000000000000000001000000 74 | # Attractor 6 is of length 1 75 | # 76 | # 1000100000000000000000000000000001000000 77 | # Attractor 7 is of length 1 78 | # 79 | # 0100100000000000000000000000000001000000 80 | # Attractor 8 is of length 1 81 | # 82 | # 0111000000000000000000000000000001000000 83 | # Attractor 9 is of length 1 84 | 85 | # 1 = CD45 86 | .n 1 1 1 87 | 1 1 88 | 0 0 89 | 90 | # 2 = CD8 91 | .n 2 1 2 92 | 1 1 93 | 0 0 94 | 95 | # 3 = TCRlig 96 | .n 3 1 3 97 | 1 1 98 | 0 0 99 | 100 | # 4 = TCRbind 101 | .n 4 2 3 11 102 | 10 1 103 | 0- 0 104 | -1 0 105 | 106 | # 5 = PAGCsk 107 | .n 5 2 7 4 108 | -0 1 109 | 1- 1 110 | 01 0 111 | 112 | # 6 = LCK 113 | .n 6 3 1 2 5 114 | 110 1 115 | 0-- 0 116 | -0- 0 117 | --1 0 118 | 119 | # 7 = Fyn 120 | .n 7 3 1 4 6 121 | 1-1 1 122 | 11- 1 123 | -00 0 124 | 0-- 0 125 | 126 | # 8 = Rlk 127 | .n 8 1 6 128 | 1 1 129 | 0 0 130 | 131 | # 9 = TCRphos 132 | .n 9 3 4 6 7 133 | 11- 1 134 | --1 1 135 | 0-0 0 136 | -00 0 137 | 138 | # 10 = ZAP70 139 | .n 10 3 6 9 11 140 | 110 1 141 | 0-- 0 142 | -0- 0 143 | --1 0 144 | 145 | # 11 = cCbl 146 | .n 11 1 10 147 | 1 1 148 | 0 0 149 | 150 | # 12 = Itk 151 | .n 12 2 10 15 152 | 11 1 153 | 0- 0 154 | -0 0 155 | 156 | # 13 = LAT 157 | .n 13 1 10 158 | 1 1 159 | 0 0 160 | 161 | # 14 = Gads 162 | .n 14 1 13 163 | 1 1 164 | 0 0 165 | 166 | # 15 = Slp76 167 | .n 15 1 14 168 | 1 1 169 | 0 0 170 | 171 | # 16 = PLCg_b 172 | .n 16 1 13 173 | 1 1 174 | 0 0 175 | 176 | # 17 = Grb2Sos 177 | .n 17 1 13 178 | 1 1 179 | 0 0 180 | 181 | # 18 = DAG 182 | .n 18 1 19 183 | 1 1 184 | 0 0 185 | 186 | # 19 = PLCg_a 187 | .n 19 5 8 10 12 15 16 188 | -1111 1 189 | 11-11 1 190 | 0-0-- 0 191 | -0--- 0 192 | ---0- 0 193 | ----0 0 194 | 195 | # 20 = Ras 196 | .n 20 2 17 21 197 | -1 1 198 | 1- 1 199 | 00 0 200 | 201 | # 21 = RasGRP1 202 | .n 21 2 18 22 203 | 11 1 204 | 0- 0 205 | -0 0 206 | 207 | # 22 = PKCth 208 | .n 22 1 18 209 | 1 1 210 | 0 0 211 | 212 | # 23 = IP3 213 | .n 23 1 19 214 | 1 1 215 | 0 0 216 | 217 | # 24 = Raf 218 | .n 24 1 20 219 | 1 1 220 | 0 0 221 | 222 | # 25 = MEK 223 | .n 25 1 24 224 | 1 1 225 | 0 0 226 | 227 | # 26 = Ca 228 | .n 26 1 23 229 | 1 1 230 | 0 0 231 | 232 | # 27 = ERK 233 | .n 27 1 25 234 | 1 1 235 | 0 0 236 | 237 | # 28 = SEK 238 | .n 28 1 22 239 | 1 1 240 | 0 0 241 | 242 | # 29 = IKK 243 | .n 29 1 22 244 | 1 1 245 | 0 0 246 | 247 | # 30 = Calcin 248 | .n 30 1 26 249 | 1 1 250 | 0 0 251 | 252 | # 31 = Rsk 253 | .n 31 1 27 254 | 1 1 255 | 0 0 256 | 257 | # 32 = Fos 258 | .n 32 1 27 259 | 1 1 260 | 0 0 261 | 262 | # 33 = JNK 263 | .n 33 1 28 264 | 1 1 265 | 0 0 266 | 267 | # 34 = Ikb 268 | .n 34 1 29 269 | 0 1 270 | 1 0 271 | 272 | # 35 = CREB 273 | .n 35 1 31 274 | 1 1 275 | 0 0 276 | 277 | # 36 = Jun 278 | .n 36 1 33 279 | 1 1 280 | 0 0 281 | 282 | # 37 = CRE 283 | .n 37 1 35 284 | 1 1 285 | 0 0 286 | 287 | # 38 = AP1 288 | .n 38 2 32 36 289 | 11 1 290 | 0- 0 291 | -0 0 292 | 293 | # 39 = NFkB 294 | .n 39 1 34 295 | 0 1 296 | 1 0 297 | 298 | # 40 = NFAT 299 | .n 40 1 30 300 | 1 1 301 | 0 0 302 | -------------------------------------------------------------------------------- /cana/datasets/bns/thelper.cnet: -------------------------------------------------------------------------------- 1 | # Boolean network model of the control of T-helper cell differentiation from 2 | # "A method for the generation of standardized qualitative dynamical systems 3 | # of regulatory networks", L. Mendoza and I. Xenarios 4 | # J. Theor. Biol. and Medical Modelling, 2006, vol. 3, no. 13 5 | 6 | #total number of nodes 7 | .v 23 8 | 9 | # labels of nodes and names of corresponding components 10 | # 1 = TCR 11 | # 2 = NFAT 12 | # 3 = IFN-\beta 13 | # 4 = IFN-\beta R 14 | # 5 = IL-18 15 | # 6 = IL-18R 16 | # 7 = IRAK 17 | # 8 = SOCS1 18 | # 9 = IL-12 19 | # 10 = IL-12R 20 | # 11 = STAT4 21 | # 12 = T-bet 22 | # 13 = IFN-\gamma 23 | # 14 = IFN-\gamma R 24 | # 15 = JAK1 25 | # 16 = STAT1 26 | # 17 = IL-4 27 | # 18 = IL-4R 28 | # 19 = STAT6 29 | # 20 = GATA3 30 | # 21 = IL-10 31 | # 22 = IL-10R 32 | # 23 = STAT3 33 | 34 | # As a result of simulation, we get the following 3 single-point attractors 35 | # corresponding to cell types Th-0, Th-1 and Th-2: 36 | # Th0: all-0 37 | # Th1: 00000001000111000000000 38 | # Th2: 00000000000000001111111 39 | 40 | # 1 = TCR 41 | .n 1 0 42 | 43 | # 2 = NFAT 44 | .n 2 1 1 45 | 1 1 46 | 0 0 47 | 48 | # 3 = IFN-\beta 49 | .n 3 0 50 | 51 | # 4 = IFN-\beta R 52 | .n 4 1 3 53 | 1 1 54 | 0 0 55 | 56 | # 5 = IL-18 57 | .n 5 0 58 | 59 | # 6 = IL-18R 60 | .n 6 2 5 19 61 | 10 1 62 | 0- 0 63 | -1 0 64 | 65 | # 7 = IRAK 66 | .n 7 1 6 67 | 1 1 68 | 0 0 69 | 70 | # 8 = SOCS1 71 | .n 8 2 12 16 72 | -1 1 73 | 1- 1 74 | 00 0 75 | 76 | # 9 = IL-12 77 | .n 9 0 78 | 79 | # 10 = IL-12R 80 | .n 10 2 9 19 81 | 10 1 82 | 0- 0 83 | -1 0 84 | 85 | # 11 = STAT4 86 | .n 11 2 10 20 87 | 10 1 88 | 0- 0 89 | -1 0 90 | 91 | # 12 = T-bet 92 | .n 12 3 12 16 20 93 | -10 1 94 | 1-0 1 95 | 00- 0 96 | --1 0 97 | 98 | # 13 = IFN-\gamma 99 | .n 13 5 2 7 11 12 23 100 | ---10 1 101 | --1-0 1 102 | -1--0 1 103 | 1---0 1 104 | 0000- 0 105 | ----1 0 106 | 107 | # 14 = IFN-\gamma R 108 | .n 14 1 13 109 | 1 1 110 | 0 0 111 | 112 | # 15 = JAK1 113 | .n 15 2 14 8 114 | 10 1 115 | 0- 0 116 | -1 0 117 | 118 | # 16 = STAT1 119 | .n 16 2 4 15 120 | -1 1 121 | 1- 1 122 | 00 0 123 | 124 | # 17 = IL-4 125 | .n 17 2 20 16 126 | 10 1 127 | 0- 0 128 | -1 0 129 | 130 | # 18 = IL-4R 131 | .n 18 2 17 8 132 | 10 1 133 | 0- 0 134 | -1 0 135 | 136 | # 19 = STAT6 137 | .n 19 1 18 138 | 1 1 139 | 0 0 140 | 141 | # 20 = GATA3 142 | .n 20 3 19 20 12 143 | -10 1 144 | 1-0 1 145 | 00- 0 146 | --1 0 147 | 148 | # 21 = IL-10 149 | .n 21 1 20 150 | 1 1 151 | 0 0 152 | 153 | # 22 = IL-10R 154 | .n 22 1 21 155 | 1 1 156 | 0 0 157 | 158 | # 23 = STAT3 159 | .n 23 1 22 160 | 1 1 161 | 0 0 162 | 163 | 164 | -------------------------------------------------------------------------------- /cana/datasets/bools.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Boolean Nodes 4 | ================================= 5 | 6 | Commonly used boolean node functions. 7 | 8 | """ 9 | # Copyright (C) 2021 by 10 | # Alex Gates 11 | # Rion Brattig Correia 12 | # All rights reserved. 13 | # MIT license. 14 | from ..boolean_network import BooleanNode 15 | 16 | 17 | def AND(): 18 | """AND boolean node. 19 | 20 | .. code:: 21 | 22 | 00 : 0 23 | 01 : 0 24 | 10 : 0 25 | 11 : 1 26 | 27 | """ 28 | return BooleanNode.from_output_list(outputs=[0, 0, 0, 1], name="AND") 29 | 30 | 31 | def OR(): 32 | """OR boolean node. 33 | 34 | .. code:: 35 | 36 | 00 : 0 37 | 01 : 1 38 | 10 : 1 39 | 11 : 1 40 | 41 | """ 42 | return BooleanNode.from_output_list(outputs=[0, 1, 1, 1], name="OR") 43 | 44 | 45 | def XOR(): 46 | """XOR boolean node. 47 | 48 | .. code:: 49 | 50 | 00 : 0 51 | 01 : 1 52 | 10 : 1 53 | 11 : 0 54 | 55 | """ 56 | return BooleanNode.from_output_list(outputs=[0, 1, 1, 0], name="XOR") 57 | 58 | 59 | def COPYx1(): 60 | """COPY :math:`x_1` boolean node. 61 | 62 | .. code:: 63 | 64 | 00 : 0 65 | 01 : 0 66 | 10 : 1 67 | 11 : 1 68 | 69 | """ 70 | return BooleanNode.from_output_list(outputs=[0, 0, 1, 1], name="COPY x_1") 71 | 72 | 73 | def CONTRADICTION(): 74 | """Contradiction boolean node. 75 | 76 | .. code:: 77 | 78 | 00 : 0 79 | 01 : 0 80 | 10 : 0 81 | 11 : 0 82 | 83 | """ 84 | return BooleanNode.from_output_list(outputs=[0, 0, 0, 0], name="CONTRADICTION") 85 | 86 | 87 | def RULE90(): 88 | """RULE 90 celular automata node. 89 | 90 | .. code:: 91 | 92 | 000 : 0 93 | 001 : 1 94 | 010 : 0 95 | 011 : 1 96 | 100 : 1 97 | 101 : 0 98 | 110 : 1 99 | 111 : 0 100 | 101 | """ 102 | return BooleanNode.from_output_list( 103 | outputs=[0, 1, 0, 1, 1, 0, 1, 0], name="RULE 90" 104 | ) 105 | 106 | 107 | def RULE110(): 108 | """RULE 110 celular automata node. 109 | 110 | .. code:: 111 | 112 | 000 : 0 113 | 001 : 1 114 | 010 : 1 115 | 011 : 1 116 | 100 : 0 117 | 101 : 1 118 | 110 : 1 119 | 111 : 0 120 | 121 | """ 122 | return BooleanNode.from_output_list( 123 | outputs=[0, 1, 1, 1, 0, 1, 1, 0], name="RULE 110" 124 | ) 125 | -------------------------------------------------------------------------------- /cana/datasets/breast_cancer.txt: -------------------------------------------------------------------------------- 1 | #Boolean network model of signal transduction in ER+ breast cancer 2 | #From Zaoudo, Jorge Gumez Tejeda, Maurizio Scaltriti, and Reka Albert. 3 | #"A network modeling approach to elucidate drug resistance mechanisms and predict combinatorial drug treatments in breast cancer." 4 | #Cancer Convergence 1.1 (2017): 5. 5 | #BOOLEAN RULES 6 | IGF1R_T*=IGF1R_T 7 | IGF1R*=IGF1R_T or (HER2 and FOXO3) or IGF1R_2 8 | IGF1R_2*=(IGF1R_T or (HER2 and FOXO3)) and not S6K and IGF1R 9 | Fulvestrant*=Fulvestrant 10 | Alpelisib*=Alpelisib 11 | Everolimus*=Everolimus 12 | Trametinib*=Trametinib 13 | Ipatasertib*=Ipatasertib 14 | Palbociclib*=Palbociclib 15 | Neratinib*=Neratinib 16 | HER2*=HER2 17 | HER3_T*=HER3_T 18 | HER3*=HER3_T or FOXO3 or HER3_2 19 | HER3_2*=FOXO3 and HER3 20 | PDK1*=PDK1 21 | mTORC2*=mTORC2 and not Everolimus 22 | SGK1_T*=SGK1_T 23 | SGK1*=SGK1_T and PDK1 and mTORC2 24 | PIM*=PIM 25 | HER2_3*=((HER3 or HER3_2) and HER2 and not Neratinib) or HER2_3_2 26 | HER2_3_2*=((HER3_2 and HER2) or (HER3 and HER2 and not MAPK_2)) and not Neratinib and HER2_3 27 | RAS*=IGF1R or IGF1R_2 or HER2_3 or HER2_3_2 or RAS_2 or RAS_3 28 | RAS_2*=((HER2_3 or HER2_3_2) and RAS) or RAS_3 29 | RAS_3*=HER2_3_2 and RAS and RAS_2 30 | MAPK*=((RAS or RAS_2 or RAS_3) and (PIP3 or PIP3_2) and not (Trametinib and not RAS_3)) or MAPK_2 31 | MAPK_2*=(RAS_2 or RAS_3) and (PIP3 or PIP3_2) and not (Trametinib and not RAS_3) and MAPK 32 | PI3K*=((IGF1R or IGF1R_2 or HER2_3 or HER2_3_2 or RAS or RAS_2 or RAS_3) and not (Alpelisib and not HER2_3_2)) or PI3K_2 33 | PI3K_2*=HER2_3_2 and not Alpelisib and PI3K 34 | PTEN*=PTEN 35 | PIP3*=((PI3K or PI3K_2) and not PTEN) or PIP3_2 36 | PIP3_2*=PI3K_2 and not PTEN and PIP3 37 | PDK1_pm*=(PIP3 or PIP3_2) 38 | mTORC2_pm*=(PIP3 or PIP3_2) and not Everolimus 39 | AKT*=((PIP3 or PIP3_2) and (PDK1_pm or mTORC2_pm) and not (Ipatasertib and not PIP3_2)) 40 | p21_p27_T*=FOXO3 or not (MYC_2 or MYC) 41 | p21_p27*=(not AKT and not PIM) or p21_p27_T 42 | cycE_CDK2_T*=E2F or E2F_2 or E2F_3 43 | cycE_CDK2*=not p21_p27 and cycE_CDK2_T 44 | KMT2D*=not AKT 45 | TSC*=not AKT and not SGK1 and not MAPK_2 46 | PRAS40*=not AKT and not PIM 47 | mTORC1*=(not TSC or not PRAS40) and not Everolimus 48 | FOXO3*=(not AKT and not SGK1 and not PIM) and not FOXO3_Ub 49 | FOXO3_Ub*=MAPK_2 50 | BIM_T*=BIM_T 51 | BCL2_T*=BCL2_T 52 | BIM*=(FOXO3 and not MAPK_2) or BIM_T 53 | BAD*= not AKT and not PIM and not (MAPK or MAPK_2) 54 | MCL1*= Translation 55 | EIF4F*=mTORC1 56 | S6K*=mTORC1 57 | Translation*=EIF4F and S6K 58 | ER*=ER 59 | ESR1*=((ER or FOXO3) and not Fulvestrant) or ESR1_2 60 | ESR1_2*=(ER and FOXO3 and not Fulvestrant) and ESR1 61 | FOXA1*= FOXO3 62 | PBX1*= PBX1 63 | ER_transcription*=(ER and (ESR1 or ESR1_2)) or ER_transcription_2 64 | ER_transcription_2*=KMT2D and FOXA1 and PBX1 and ESR1_2 and ER and ER_transcription 65 | MYC*=ER_transcription or MYC_2 66 | MYC_2*=ER_transcription_2 and MYC 67 | cyclinD*=MYC or cyclinD_2 68 | cyclinD_2*=MYC_2 and cyclinD 69 | BCL2*=ER_transcription_2 or BCL2_T 70 | CDK46*=not Palbociclib 71 | cycD_CDK46*=((cyclinD or cyclinD_2) and CDK46) or cycD_CDK46_2 72 | cycD_CDK46_2*=(cyclinD_2) and CDK46 and cycD_CDK46 73 | pRb*=(cycD_CDK46_2 or cycD_CDK46) or cycE_CDK2 or pRb_2 or pRb_3 74 | pRb_2*=(((cycD_CDK46 and cycE_CDK2) or cycD_CDK46_2) and pRb) or pRb_3 75 | pRb_3*=cycD_CDK46_2 and cycE_CDK2 and pRb_2 and pRb 76 | E2F*=pRb or E2F_2 or E2F_3 77 | E2F_2*=(pRb_2 and E2F) or E2F_3 78 | E2F_3*=(pRb_3 or (pRb_2 and E2F_3)) and E2F_2 and E2F 79 | Proliferation*=Translation or E2F or E2F_2 or E2F_3 80 | Proliferation_2*=Translation or E2F_2 or E2F_3 81 | Proliferation_3*=(Translation and E2F_2) or E2F_3 82 | Proliferation_4*=Translation and E2F_3 83 | Apoptosis*=(BIM and not (MCL1 and BCL2)) or (BIM and BAD) or (BAD and not (MCL1 and BCL2)) or Apoptosis 84 | Apoptosis_2*=(BIM and BAD and not (MCL1 and BCL2)) or Apoptosis_2 85 | Apoptosis_3*=((BIM and BAD and not (MCL1 or BCL2))) or Apoptosis_3 -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Apoptosis Network.txt: -------------------------------------------------------------------------------- 1 | .v 41 2 | 3 | .l 1 Cas3 4 | .l 2 Cas12 5 | .l 3 IAP 6 | .l 4 cFLIP 7 | .l 5 TRADD 8 | .l 6 TNFR2 9 | .l 7 PTEN 10 | .l 8 APC 11 | .l 9 FADD 12 | .l 10 Apaf1 13 | .l 11 Mito 14 | .l 12 JNK 15 | .l 13 Mdm2 16 | .l 14 Cas8 17 | .l 15 p53 18 | .l 16 Apoptosis 19 | .l 17 NFkB 20 | .l 18 PIP3 21 | .l 19 Cas7 22 | .l 20 PI3K 23 | .l 21 JNKK 24 | .l 22 Cas6 25 | .l 23 MEKK1 26 | .l 24 TNFR1 27 | .l 25 NIK 28 | .l 26 IKK 29 | .l 27 IkB 30 | .l 28 TRAF2 31 | .l 29 TRAF 32 | .l 30 AKT 33 | .l 31 PIP2 34 | .l 32 GFR 35 | .l 33 A20 36 | .l 34 RIP 37 | .l 35 BID 38 | .l 36 Cas9 39 | .l 37 BclX 40 | .l 38 DNADamageEvent 41 | .l 39 BAD 42 | .l 40 TNF 43 | .l 41 GF 44 | 45 | # 1 Cas3 46 | .n 1 4 3 8 14 22 47 | 1111 0 48 | 1110 0 49 | 1101 0 50 | 1100 0 51 | 1011 0 52 | 1010 0 53 | 1001 0 54 | 1000 0 55 | 0111 1 56 | 0110 1 57 | 0101 1 58 | 0100 1 59 | 0011 1 60 | 0010 1 61 | 0001 1 62 | 0000 0 63 | 64 | # 2 Cas12 65 | .n 2 1 19 66 | 1 1 67 | 0 0 68 | 69 | # 3 IAP 70 | .n 3 4 1 11 17 22 71 | 1111 0 72 | 1110 0 73 | 1101 0 74 | 1100 0 75 | 1011 0 76 | 1010 1 77 | 1001 0 78 | 1000 0 79 | 0111 0 80 | 0110 0 81 | 0101 0 82 | 0100 0 83 | 0011 1 84 | 0010 1 85 | 0001 0 86 | 0000 0 87 | 88 | # 4 cFLIP 89 | .n 4 1 29 90 | 1 1 91 | 0 0 92 | 93 | # 5 TRADD 94 | .n 5 1 24 95 | 1 1 96 | 0 0 97 | 98 | # 6 TNFR2 99 | .n 6 1 40 100 | 1 1 101 | 0 0 102 | 103 | # 7 PTEN 104 | .n 7 1 15 105 | 1 1 106 | 0 0 107 | 108 | # 8 APC 109 | .n 8 4 3 10 11 36 110 | 1111 0 111 | 1110 0 112 | 1101 0 113 | 1100 0 114 | 1011 0 115 | 1010 0 116 | 1001 0 117 | 1000 0 118 | 0111 1 119 | 0110 0 120 | 0101 0 121 | 0100 0 122 | 0011 0 123 | 0010 0 124 | 0001 0 125 | 0000 0 126 | 127 | # 9 FADD 128 | .n 9 1 5 129 | 1 1 130 | 0 0 131 | 132 | # 10 Apaf1 133 | .n 10 1 15 134 | 1 1 135 | 0 0 136 | 137 | # 11 Mito 138 | .n 11 2 35 37 139 | 11 0 140 | 10 1 141 | 01 0 142 | 00 0 143 | 144 | # 12 JNK 145 | .n 12 1 21 146 | 1 1 147 | 0 0 148 | 149 | # 13 Mdm2 150 | .n 13 2 15 30 151 | 11 1 152 | 10 1 153 | 01 1 154 | 00 0 155 | 156 | # 14 Cas8 157 | .n 14 3 4 9 22 158 | 111 0 159 | 110 0 160 | 101 0 161 | 100 0 162 | 011 1 163 | 010 1 164 | 001 1 165 | 000 0 166 | 167 | # 15 p53 168 | .n 15 3 12 13 38 169 | 111 0 170 | 110 0 171 | 101 1 172 | 100 1 173 | 011 0 174 | 010 0 175 | 001 1 176 | 000 0 177 | 178 | # 16 Apoptosis 179 | .n 16 1 38 180 | 1 1 181 | 0 0 182 | 183 | # 17 NFkB 184 | .n 17 1 27 185 | 1 0 186 | 0 1 187 | 188 | # 18 PIP3 189 | .n 18 3 7 20 31 190 | 111 0 191 | 110 0 192 | 101 0 193 | 100 0 194 | 011 1 195 | 010 0 196 | 001 0 197 | 000 0 198 | 199 | # 19 Cas7 200 | .n 19 3 3 8 14 201 | 111 0 202 | 110 0 203 | 101 0 204 | 100 0 205 | 011 1 206 | 010 1 207 | 001 1 208 | 000 0 209 | 210 | # 20 PI3K 211 | .n 20 1 32 212 | 1 1 213 | 0 0 214 | 215 | # 21 JNKK 216 | .n 21 2 23 30 217 | 11 0 218 | 10 1 219 | 01 0 220 | 00 0 221 | 222 | # 22 Cas6 223 | .n 22 2 1 3 224 | 11 0 225 | 10 1 226 | 01 0 227 | 00 0 228 | 229 | # 23 MEKK1 230 | .n 23 1 34 231 | 1 1 232 | 0 0 233 | 234 | # 24 TNFR1 235 | .n 24 1 40 236 | 1 1 237 | 0 0 238 | 239 | # 25 NIK 240 | .n 25 1 28 241 | 1 1 242 | 0 0 243 | 244 | # 26 IKK 245 | .n 26 3 25 30 33 246 | 111 0 247 | 110 1 248 | 101 0 249 | 100 1 250 | 011 0 251 | 010 1 252 | 001 0 253 | 000 0 254 | 255 | # 27 IkB 256 | .n 27 2 17 26 257 | 11 0 258 | 10 1 259 | 01 0 260 | 00 0 261 | 262 | # 28 TRAF2 263 | .n 28 2 6 34 264 | 11 1 265 | 10 1 266 | 01 1 267 | 00 0 268 | 269 | # 29 TRAF 270 | .n 29 1 5 271 | 1 1 272 | 0 0 273 | 274 | # 30 AKT 275 | .n 30 1 18 276 | 1 1 277 | 0 0 278 | 279 | # 31 PIP2 280 | .n 31 1 32 281 | 1 1 282 | 0 0 283 | 284 | # 32 GFR 285 | .n 32 1 41 286 | 1 1 287 | 0 0 288 | 289 | # 33 A20 290 | .n 33 1 17 291 | 1 1 292 | 0 0 293 | 294 | # 34 RIP 295 | .n 34 1 5 296 | 1 1 297 | 0 0 298 | 299 | # 35 BID 300 | .n 35 4 12 14 15 37 301 | 1111 0 302 | 1110 1 303 | 1101 0 304 | 1100 0 305 | 1011 0 306 | 1010 1 307 | 1001 0 308 | 1000 0 309 | 0111 0 310 | 0110 1 311 | 0101 0 312 | 0100 0 313 | 0011 0 314 | 0010 0 315 | 0001 0 316 | 0000 0 317 | 318 | # 36 Cas9 319 | .n 36 4 1 2 3 30 320 | 1111 0 321 | 1110 0 322 | 1101 0 323 | 1100 1 324 | 1011 0 325 | 1010 0 326 | 1001 0 327 | 1000 1 328 | 0111 0 329 | 0110 0 330 | 0101 0 331 | 0100 1 332 | 0011 0 333 | 0010 0 334 | 0001 0 335 | 0000 0 336 | 337 | # 37 BclX 338 | .n 37 3 15 17 39 339 | 111 0 340 | 110 0 341 | 101 0 342 | 100 0 343 | 011 0 344 | 010 1 345 | 001 0 346 | 000 0 347 | 348 | # 38 DNADamageEvent 349 | .n 38 1 1 350 | 1 1 351 | 0 0 352 | 353 | # 39 BAD 354 | .n 39 2 15 30 355 | 11 0 356 | 10 1 357 | 01 0 358 | 00 0 359 | 360 | # 40 TNF 361 | .n 40 0 362 | 363 | # 41 GF 364 | .n 41 0 365 | 366 | .e End of file 367 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Aurora Kinase A in Neuroblastoma.txt: -------------------------------------------------------------------------------- 1 | .v 23 2 | 3 | .l 1 PP2A 4 | .l 2 STMN 5 | .l 3 CDC25B 6 | .l 4 CentrosomeMat 7 | .l 5 PLK1 8 | .l 6 CDK1CCNBComplex 9 | .l 7 hCPEB 10 | .l 8 TPX2 11 | .l 9 AURKAActive 12 | .l 10 NEDD9 13 | .l 11 ENSA 14 | .l 12 Cytokinesis 15 | .l 13 PP1 16 | .l 14 MT 17 | .l 15 SpindleAssembly 18 | .l 16 WEE1 19 | .l 17 BORA 20 | .l 18 AURKAPresent 21 | .l 19 GWL_MASTL 22 | .l 20 AJUBA 23 | .l 21 GSK3B 24 | .l 22 MTCanAct 25 | .l 23 STMNCanAct 26 | 27 | # 1 PP2A 28 | .n 1 2 11 13 29 | 11 0 30 | 10 0 31 | 01 1 32 | 00 0 33 | 34 | # 2 STMN 35 | .n 2 1 9 36 | 1 0 37 | 0 1 38 | 39 | # 3 CDC25B 40 | .n 3 3 5 9 12 41 | 111 0 42 | 110 1 43 | 101 0 44 | 100 1 45 | 011 0 46 | 010 1 47 | 001 0 48 | 000 0 49 | 50 | # 4 CentrosomeMat 51 | .n 4 2 6 15 52 | 11 0 53 | 10 1 54 | 01 0 55 | 00 0 56 | 57 | # 5 PLK1 58 | .n 5 5 2 9 14 22 23 59 | 11111 1 60 | 11110 1 61 | 11101 1 62 | 11100 1 63 | 11011 1 64 | 11010 1 65 | 11001 1 66 | 11000 1 67 | 10111 1 68 | 10110 1 69 | 10101 0 70 | 10100 0 71 | 10011 0 72 | 10010 0 73 | 10001 0 74 | 10000 0 75 | 01111 1 76 | 01110 1 77 | 01101 1 78 | 01100 1 79 | 01011 1 80 | 01010 1 81 | 01001 1 82 | 01000 1 83 | 00111 1 84 | 00110 1 85 | 00101 1 86 | 00100 0 87 | 00011 1 88 | 00010 0 89 | 00001 1 90 | 00000 0 91 | 92 | # 6 CDK1CCNBComplex 93 | .n 6 4 3 7 12 16 94 | 1111 0 95 | 1110 0 96 | 1101 1 97 | 1100 1 98 | 1011 0 99 | 1010 0 100 | 1001 1 101 | 1000 1 102 | 0111 0 103 | 0110 0 104 | 0101 1 105 | 0100 1 106 | 0011 0 107 | 0010 0 108 | 0001 0 109 | 0000 1 110 | 111 | # 7 hCPEB 112 | .n 7 1 9 113 | 1 1 114 | 0 0 115 | 116 | # 8 TPX2 117 | .n 8 1 5 118 | 1 1 119 | 0 0 120 | 121 | # 9 AURKAActive 122 | .n 9 7 8 9 10 13 17 18 20 123 | 1111111 0 124 | 1111110 0 125 | 1111101 0 126 | 1111100 0 127 | 1111011 0 128 | 1111010 0 129 | 1111001 0 130 | 1111000 0 131 | 1110111 1 132 | 1110110 1 133 | 1110101 0 134 | 1110100 0 135 | 1110011 1 136 | 1110010 1 137 | 1110001 0 138 | 1110000 0 139 | 1101111 0 140 | 1101110 0 141 | 1101101 0 142 | 1101100 0 143 | 1101011 0 144 | 1101010 0 145 | 1101001 0 146 | 1101000 0 147 | 1100111 1 148 | 1100110 1 149 | 1100101 0 150 | 1100100 0 151 | 1100011 1 152 | 1100010 1 153 | 1100001 0 154 | 1100000 0 155 | 1011111 1 156 | 1011110 1 157 | 1011101 0 158 | 1011100 0 159 | 1011011 1 160 | 1011010 1 161 | 1011001 0 162 | 1011000 0 163 | 1010111 1 164 | 1010110 1 165 | 1010101 0 166 | 1010100 0 167 | 1010011 1 168 | 1010010 1 169 | 1010001 0 170 | 1010000 0 171 | 1001111 1 172 | 1001110 1 173 | 1001101 0 174 | 1001100 0 175 | 1001011 1 176 | 1001010 1 177 | 1001001 0 178 | 1001000 0 179 | 1000111 1 180 | 1000110 1 181 | 1000101 0 182 | 1000100 0 183 | 1000011 1 184 | 1000010 1 185 | 1000001 0 186 | 1000000 0 187 | 0111111 0 188 | 0111110 0 189 | 0111101 0 190 | 0111100 0 191 | 0111011 0 192 | 0111010 0 193 | 0111001 0 194 | 0111000 0 195 | 0110111 1 196 | 0110110 0 197 | 0110101 0 198 | 0110100 0 199 | 0110011 1 200 | 0110010 0 201 | 0110001 0 202 | 0110000 0 203 | 0101111 0 204 | 0101110 0 205 | 0101101 0 206 | 0101100 0 207 | 0101011 0 208 | 0101010 0 209 | 0101001 0 210 | 0101000 0 211 | 0100111 1 212 | 0100110 0 213 | 0100101 0 214 | 0100100 0 215 | 0100011 0 216 | 0100010 0 217 | 0100001 0 218 | 0100000 0 219 | 0011111 1 220 | 0011110 0 221 | 0011101 0 222 | 0011100 0 223 | 0011011 1 224 | 0011010 0 225 | 0011001 0 226 | 0011000 0 227 | 0010111 1 228 | 0010110 0 229 | 0010101 0 230 | 0010100 0 231 | 0010011 1 232 | 0010010 0 233 | 0010001 0 234 | 0010000 0 235 | 0001111 1 236 | 0001110 0 237 | 0001101 0 238 | 0001100 0 239 | 0001011 0 240 | 0001010 0 241 | 0001001 0 242 | 0001000 0 243 | 0000111 1 244 | 0000110 0 245 | 0000101 0 246 | 0000100 0 247 | 0000011 0 248 | 0000010 0 249 | 0000001 0 250 | 0000000 0 251 | 252 | # 10 NEDD9 253 | .n 10 1 9 254 | 1 1 255 | 0 0 256 | 257 | # 11 ENSA 258 | .n 11 1 19 259 | 1 1 260 | 0 0 261 | 262 | # 12 Cytokinesis 263 | .n 12 2 4 15 264 | 11 0 265 | 10 0 266 | 01 1 267 | 00 0 268 | 269 | # 13 PP1 270 | .n 13 3 6 9 12 271 | 111 0 272 | 110 0 273 | 101 0 274 | 100 0 275 | 011 0 276 | 010 0 277 | 001 0 278 | 000 1 279 | 280 | # 14 MT 281 | .n 14 1 2 282 | 1 0 283 | 0 1 284 | 285 | # 15 SpindleAssembly 286 | .n 15 2 4 12 287 | 11 0 288 | 10 1 289 | 01 0 290 | 00 0 291 | 292 | # 16 WEE1 293 | .n 16 1 5 294 | 1 0 295 | 0 1 296 | 297 | # 17 BORA 298 | .n 17 3 5 12 21 299 | 111 0 300 | 110 0 301 | 101 1 302 | 100 0 303 | 011 1 304 | 010 0 305 | 001 1 306 | 000 0 307 | 308 | # 18 AURKAPresent 309 | .n 18 1 1 310 | 1 0 311 | 0 1 312 | 313 | # 19 GWL_MASTL 314 | .n 19 2 1 6 315 | 11 0 316 | 10 0 317 | 01 1 318 | 00 0 319 | 320 | # 20 AJUBA 321 | .n 20 0 322 | 323 | # 21 GSK3B 324 | .n 21 0 325 | 326 | # 22 MTCanAct 327 | .n 22 0 328 | 329 | # 23 STMNCanAct 330 | .n 23 0 331 | 332 | .e End of file 333 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/B cell differentiation.txt: -------------------------------------------------------------------------------- 1 | .v 22 2 | 3 | .l 1 STAT6 4 | .l 2 IL-21R 5 | .l 3 NF-kB 6 | .l 4 BCR 7 | .l 5 IL-2R 8 | .l 6 Bach2 9 | .l 7 STAT3 10 | .l 8 CD40 11 | .l 9 Pax5 12 | .l 10 Bcl6 13 | .l 11 ERK 14 | .l 12 Blimp1 15 | .l 13 STAT5 16 | .l 14 IL-4R 17 | .l 15 AID 18 | .l 16 Irf4 19 | .l 17 XBP1 20 | .l 18 CD40L 21 | .l 19 IL-21 22 | .l 20 IL-2 23 | .l 21 Ag 24 | .l 22 IL-4 25 | 26 | # 1 STAT6 27 | .n 1 1 14 28 | 1 1 29 | 0 0 30 | 31 | # 2 IL-21R 32 | .n 2 1 19 33 | 1 1 34 | 0 0 35 | 36 | # 3 NF-kB 37 | .n 3 1 8 38 | 1 1 39 | 0 0 40 | 41 | # 4 BCR 42 | .n 4 1 21 43 | 1 1 44 | 0 0 45 | 46 | # 5 IL-2R 47 | .n 5 1 20 48 | 1 1 49 | 0 0 50 | 51 | # 6 Bach2 52 | .n 6 2 9 12 53 | 11 0 54 | 10 1 55 | 01 0 56 | 00 0 57 | 58 | # 7 STAT3 59 | .n 7 1 2 60 | 1 1 61 | 0 0 62 | 63 | # 8 CD40 64 | .n 8 1 18 65 | 1 1 66 | 0 0 67 | 68 | # 9 Pax5 69 | .n 9 4 9 11 12 16 70 | 1111 0 71 | 1110 0 72 | 1101 0 73 | 1100 0 74 | 1011 0 75 | 1010 0 76 | 1001 1 77 | 1000 1 78 | 0111 0 79 | 0110 0 80 | 0101 0 81 | 0100 0 82 | 0011 0 83 | 0010 0 84 | 0001 0 85 | 0000 1 86 | 87 | # 10 Bcl6 88 | .n 10 7 1 9 10 11 12 13 16 89 | 1111111 0 90 | 1111110 0 91 | 1111101 0 92 | 1111100 0 93 | 1111011 0 94 | 1111010 0 95 | 1111001 0 96 | 1111000 0 97 | 1110111 0 98 | 1110110 0 99 | 1110101 0 100 | 1110100 0 101 | 1110011 0 102 | 1110010 1 103 | 1110001 0 104 | 1110000 1 105 | 1101111 0 106 | 1101110 0 107 | 1101101 0 108 | 1101100 0 109 | 1101011 0 110 | 1101010 0 111 | 1101001 0 112 | 1101000 0 113 | 1100111 0 114 | 1100110 0 115 | 1100101 0 116 | 1100100 0 117 | 1100011 0 118 | 1100010 1 119 | 1100001 0 120 | 1100000 1 121 | 1011111 0 122 | 1011110 0 123 | 1011101 0 124 | 1011100 0 125 | 1011011 0 126 | 1011010 0 127 | 1011001 0 128 | 1011000 0 129 | 1010111 0 130 | 1010110 0 131 | 1010101 0 132 | 1010100 0 133 | 1010011 0 134 | 1010010 1 135 | 1010001 0 136 | 1010000 1 137 | 1001111 0 138 | 1001110 0 139 | 1001101 0 140 | 1001100 0 141 | 1001011 0 142 | 1001010 0 143 | 1001001 0 144 | 1001000 0 145 | 1000111 0 146 | 1000110 0 147 | 1000101 0 148 | 1000100 0 149 | 1000011 0 150 | 1000010 1 151 | 1000001 0 152 | 1000000 1 153 | 0111111 0 154 | 0111110 0 155 | 0111101 0 156 | 0111100 0 157 | 0111011 0 158 | 0111010 0 159 | 0111001 0 160 | 0111000 0 161 | 0110111 0 162 | 0110110 0 163 | 0110101 0 164 | 0110100 0 165 | 0110011 0 166 | 0110010 1 167 | 0110001 0 168 | 0110000 1 169 | 0101111 0 170 | 0101110 0 171 | 0101101 0 172 | 0101100 0 173 | 0101011 0 174 | 0101010 0 175 | 0101001 0 176 | 0101000 0 177 | 0100111 0 178 | 0100110 0 179 | 0100101 0 180 | 0100100 0 181 | 0100011 0 182 | 0100010 1 183 | 0100001 0 184 | 0100000 0 185 | 0011111 0 186 | 0011110 0 187 | 0011101 0 188 | 0011100 0 189 | 0011011 0 190 | 0011010 0 191 | 0011001 0 192 | 0011000 0 193 | 0010111 0 194 | 0010110 0 195 | 0010101 0 196 | 0010100 0 197 | 0010011 0 198 | 0010010 1 199 | 0010001 0 200 | 0010000 0 201 | 0001111 0 202 | 0001110 0 203 | 0001101 0 204 | 0001100 0 205 | 0001011 0 206 | 0001010 0 207 | 0001001 0 208 | 0001000 0 209 | 0000111 0 210 | 0000110 0 211 | 0000101 0 212 | 0000100 0 213 | 0000011 0 214 | 0000010 1 215 | 0000001 0 216 | 0000000 0 217 | 218 | # 11 ERK 219 | .n 11 1 4 220 | 1 1 221 | 0 0 222 | 223 | # 12 Blimp1 224 | .n 12 6 6 7 9 10 11 16 225 | 111111 0 226 | 111110 0 227 | 111101 0 228 | 111100 0 229 | 111011 0 230 | 111010 0 231 | 111001 0 232 | 111000 0 233 | 110111 0 234 | 110110 0 235 | 110101 0 236 | 110100 0 237 | 110011 0 238 | 110010 0 239 | 110001 0 240 | 110000 0 241 | 101111 0 242 | 101110 0 243 | 101101 0 244 | 101100 0 245 | 101011 0 246 | 101010 0 247 | 101001 0 248 | 101000 0 249 | 100111 0 250 | 100110 0 251 | 100101 0 252 | 100100 0 253 | 100011 0 254 | 100010 0 255 | 100001 0 256 | 100000 0 257 | 011111 0 258 | 011110 0 259 | 011101 0 260 | 011100 0 261 | 011011 0 262 | 011010 0 263 | 011001 0 264 | 011000 0 265 | 010111 0 266 | 010110 0 267 | 010101 0 268 | 010100 0 269 | 010011 1 270 | 010010 1 271 | 010001 1 272 | 010000 1 273 | 001111 0 274 | 001110 0 275 | 001101 0 276 | 001100 0 277 | 001011 0 278 | 001010 0 279 | 001001 0 280 | 001000 0 281 | 000111 0 282 | 000110 0 283 | 000101 0 284 | 000100 0 285 | 000011 1 286 | 000010 1 287 | 000001 1 288 | 000000 0 289 | 290 | # 13 STAT5 291 | .n 13 1 5 292 | 1 1 293 | 0 0 294 | 295 | # 14 IL-4R 296 | .n 14 1 22 297 | 1 1 298 | 0 0 299 | 300 | # 15 AID 301 | .n 15 4 1 3 9 12 302 | 1111 0 303 | 1110 1 304 | 1101 0 305 | 1100 1 306 | 1011 0 307 | 1010 1 308 | 1001 0 309 | 1000 1 310 | 0111 0 311 | 0110 1 312 | 0101 0 313 | 0100 0 314 | 0011 0 315 | 0010 0 316 | 0001 0 317 | 0000 0 318 | 319 | # 16 Irf4 320 | .n 16 4 3 10 12 16 321 | 1111 1 322 | 1110 1 323 | 1101 1 324 | 1100 1 325 | 1011 1 326 | 1010 1 327 | 1001 1 328 | 1000 1 329 | 0111 0 330 | 0110 0 331 | 0101 0 332 | 0100 0 333 | 0011 1 334 | 0010 1 335 | 0001 1 336 | 0000 0 337 | 338 | # 17 XBP1 339 | .n 17 2 9 12 340 | 11 0 341 | 10 0 342 | 01 1 343 | 00 0 344 | 345 | # 18 CD40L 346 | .n 18 0 347 | 348 | # 19 IL-21 349 | .n 19 0 350 | 351 | # 20 IL-2 352 | .n 20 0 353 | 354 | # 21 Ag 355 | .n 21 0 356 | 357 | # 22 IL-4 358 | .n 22 0 359 | 360 | .e End of file 361 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/BT474 Breast Cell Line Short-term ErbB Network.txt: -------------------------------------------------------------------------------- 1 | .v 16 2 | 3 | .l 1 PKCa 4 | .l 2 MEK1_2 5 | .l 3 p70S6K 6 | .l 4 mTOR 7 | .l 5 ERK1_2 8 | .l 6 PDK1 9 | .l 7 AKT 10 | .l 8 ERBB3 11 | .l 9 ERBB1 12 | .l 10 ERBB2 13 | .l 11 PLCg 14 | .l 12 trastuzumab 15 | .l 13 pertuzumab 16 | .l 14 erlotinib 17 | .l 15 HRG 18 | .l 16 EGF 19 | 20 | # 1 PKCa 21 | .n 1 2 1 11 22 | 11 1 23 | 10 1 24 | 01 1 25 | 00 0 26 | 27 | # 2 MEK1_2 28 | .n 2 4 2 8 9 10 29 | 1111 1 30 | 1110 1 31 | 1101 1 32 | 1100 1 33 | 1011 1 34 | 1010 1 35 | 1001 1 36 | 1000 1 37 | 0111 1 38 | 0110 1 39 | 0101 1 40 | 0100 1 41 | 0011 1 42 | 0010 1 43 | 0001 1 44 | 0000 0 45 | 46 | # 3 p70S6K 47 | .n 3 4 3 4 5 7 48 | 1111 1 49 | 1110 1 50 | 1101 1 51 | 1100 1 52 | 1011 1 53 | 1010 1 54 | 1001 1 55 | 1000 1 56 | 0111 1 57 | 0110 1 58 | 0101 1 59 | 0100 1 60 | 0011 1 61 | 0010 1 62 | 0001 1 63 | 0000 0 64 | 65 | # 4 mTOR 66 | .n 4 3 4 7 13 67 | 111 1 68 | 110 1 69 | 101 1 70 | 100 1 71 | 011 1 72 | 010 1 73 | 001 1 74 | 000 0 75 | 76 | # 5 ERK1_2 77 | .n 5 4 2 5 13 16 78 | 1111 1 79 | 1110 1 80 | 1101 1 81 | 1100 1 82 | 1011 1 83 | 1010 1 84 | 1001 1 85 | 1000 1 86 | 0111 1 87 | 0110 1 88 | 0101 1 89 | 0100 1 90 | 0011 1 91 | 0010 1 92 | 0001 1 93 | 0000 0 94 | 95 | # 6 PDK1 96 | .n 6 5 2 6 8 9 10 97 | 11111 1 98 | 11110 1 99 | 11101 1 100 | 11100 1 101 | 11011 1 102 | 11010 1 103 | 11001 1 104 | 11000 1 105 | 10111 1 106 | 10110 1 107 | 10101 1 108 | 10100 1 109 | 10011 1 110 | 10010 1 111 | 10001 1 112 | 10000 1 113 | 01111 1 114 | 01110 1 115 | 01101 1 116 | 01100 1 117 | 01011 1 118 | 01010 1 119 | 01001 1 120 | 01000 1 121 | 00111 1 122 | 00110 1 123 | 00101 1 124 | 00100 1 125 | 00011 1 126 | 00010 1 127 | 00001 1 128 | 00000 0 129 | 130 | # 7 AKT 131 | .n 7 4 4 6 7 8 132 | 1111 1 133 | 1110 1 134 | 1101 1 135 | 1100 1 136 | 1011 1 137 | 1010 1 138 | 1001 1 139 | 1000 1 140 | 0111 1 141 | 0110 1 142 | 0101 1 143 | 0100 1 144 | 0011 1 145 | 0010 1 146 | 0001 1 147 | 0000 0 148 | 149 | # 8 ERBB3 150 | .n 8 4 8 13 14 15 151 | 1111 0 152 | 1110 0 153 | 1101 0 154 | 1100 0 155 | 1011 0 156 | 1010 0 157 | 1001 1 158 | 1000 1 159 | 0111 0 160 | 0110 0 161 | 0101 0 162 | 0100 0 163 | 0011 0 164 | 0010 0 165 | 0001 1 166 | 0000 0 167 | 168 | # 9 ERBB1 169 | .n 9 5 9 11 13 14 16 170 | 11111 0 171 | 11110 0 172 | 11101 0 173 | 11100 0 174 | 11011 0 175 | 11010 0 176 | 11001 1 177 | 11000 1 178 | 10111 0 179 | 10110 0 180 | 10101 0 181 | 10100 0 182 | 10011 0 183 | 10010 0 184 | 10001 1 185 | 10000 1 186 | 01111 0 187 | 01110 0 188 | 01101 0 189 | 01100 0 190 | 01011 0 191 | 01010 0 192 | 01001 1 193 | 01000 1 194 | 00111 0 195 | 00110 0 196 | 00101 0 197 | 00100 0 198 | 00011 0 199 | 00010 0 200 | 00001 1 201 | 00000 0 202 | 203 | # 10 ERBB2 204 | .n 10 6 8 10 12 13 14 16 205 | 111111 0 206 | 111110 0 207 | 111101 0 208 | 111100 0 209 | 111011 0 210 | 111010 0 211 | 111001 0 212 | 111000 0 213 | 110111 0 214 | 110110 0 215 | 110101 0 216 | 110100 0 217 | 110011 0 218 | 110010 0 219 | 110001 1 220 | 110000 1 221 | 101111 0 222 | 101110 0 223 | 101101 0 224 | 101100 0 225 | 101011 0 226 | 101010 0 227 | 101001 0 228 | 101000 0 229 | 100111 0 230 | 100110 0 231 | 100101 0 232 | 100100 0 233 | 100011 0 234 | 100010 0 235 | 100001 1 236 | 100000 1 237 | 011111 0 238 | 011110 0 239 | 011101 0 240 | 011100 0 241 | 011011 0 242 | 011010 0 243 | 011001 0 244 | 011000 0 245 | 010111 0 246 | 010110 0 247 | 010101 0 248 | 010100 0 249 | 010011 0 250 | 010010 0 251 | 010001 1 252 | 010000 1 253 | 001111 0 254 | 001110 0 255 | 001101 0 256 | 001100 0 257 | 001011 0 258 | 001010 0 259 | 001001 0 260 | 001000 0 261 | 000111 0 262 | 000110 0 263 | 000101 0 264 | 000100 0 265 | 000011 0 266 | 000010 0 267 | 000001 1 268 | 000000 0 269 | 270 | # 11 PLCg 271 | .n 11 5 8 9 10 11 16 272 | 11111 1 273 | 11110 1 274 | 11101 1 275 | 11100 1 276 | 11011 1 277 | 11010 1 278 | 11001 1 279 | 11000 1 280 | 10111 1 281 | 10110 1 282 | 10101 1 283 | 10100 1 284 | 10011 1 285 | 10010 1 286 | 10001 1 287 | 10000 1 288 | 01111 1 289 | 01110 1 290 | 01101 1 291 | 01100 1 292 | 01011 1 293 | 01010 1 294 | 01001 1 295 | 01000 1 296 | 00111 1 297 | 00110 1 298 | 00101 1 299 | 00100 1 300 | 00011 1 301 | 00010 1 302 | 00001 1 303 | 00000 0 304 | 305 | # 12 trastuzumab 306 | .n 12 0 307 | 308 | # 13 pertuzumab 309 | .n 13 0 310 | 311 | # 14 erlotinib 312 | .n 14 0 313 | 314 | # 15 HRG 315 | .n 15 0 316 | 317 | # 16 EGF 318 | .n 16 0 319 | 320 | .e End of file 321 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Bordetella bronchiseptica.txt: -------------------------------------------------------------------------------- 1 | .v 33 2 | 3 | .l 1 IFNgI 4 | .l 2 IgA 5 | .l 3 IL10II 6 | .l 4 IgG 7 | .l 5 T0 8 | .l 6 IL4I 9 | .l 7 TTSSII 10 | .l 8 Th1II 11 | .l 9 IL10I 12 | .l 10 AP 13 | .l 11 EC 14 | .l 12 Th2I 15 | .l 13 Bb 16 | .l 14 PIC 17 | .l 15 TrII 18 | .l 16 MPI 19 | .l 17 C 20 | .l 18 Th2II 21 | .l 19 TrI 22 | .l 20 Oag 23 | .l 21 IL12II 24 | .l 22 AgAb 25 | .l 23 DCI 26 | .l 24 DCII 27 | .l 25 IFNgII 28 | .l 26 TTSSI 29 | .l 27 BC 30 | .l 28 NE 31 | .l 29 IL4II 32 | .l 30 PH 33 | .l 31 IL12I 34 | .l 32 DP 35 | .l 33 Th1I 36 | 37 | # 1 IFNgI 38 | .n 1 5 6 9 16 23 33 39 | 11111 0 40 | 11110 0 41 | 11101 0 42 | 11100 0 43 | 11011 0 44 | 11010 0 45 | 11001 0 46 | 11000 0 47 | 10111 0 48 | 10110 0 49 | 10101 0 50 | 10100 0 51 | 10011 0 52 | 10010 0 53 | 10001 0 54 | 10000 0 55 | 01111 1 56 | 01110 1 57 | 01101 1 58 | 01100 1 59 | 01011 1 60 | 01010 1 61 | 01001 0 62 | 01000 0 63 | 00111 1 64 | 00110 1 65 | 00101 1 66 | 00100 1 67 | 00011 1 68 | 00010 1 69 | 00001 1 70 | 00000 0 71 | 72 | # 2 IgA 73 | .n 2 3 2 13 27 74 | 111 1 75 | 110 1 76 | 101 0 77 | 100 0 78 | 011 1 79 | 010 0 80 | 001 0 81 | 000 0 82 | 83 | # 3 IL10II 84 | .n 3 1 9 85 | 1 1 86 | 0 0 87 | 88 | # 4 IgG 89 | .n 4 2 4 27 90 | 11 1 91 | 10 1 92 | 01 1 93 | 00 0 94 | 95 | # 5 T0 96 | .n 5 1 24 97 | 1 1 98 | 0 0 99 | 100 | # 6 IL4I 101 | .n 6 1 29 102 | 1 1 103 | 0 0 104 | 105 | # 7 TTSSII 106 | .n 7 1 26 107 | 1 1 108 | 0 0 109 | 110 | # 8 Th1II 111 | .n 8 3 5 21 24 112 | 111 1 113 | 110 0 114 | 101 0 115 | 100 0 116 | 011 0 117 | 010 0 118 | 001 0 119 | 000 0 120 | 121 | # 9 IL10I 122 | .n 9 4 12 16 19 26 123 | 1111 1 124 | 1110 1 125 | 1101 1 126 | 1100 1 127 | 1011 1 128 | 1010 1 129 | 1001 1 130 | 1000 0 131 | 0111 1 132 | 0110 1 133 | 0101 1 134 | 0100 1 135 | 0011 1 136 | 0010 1 137 | 0001 0 138 | 0000 0 139 | 140 | # 10 AP 141 | .n 10 6 4 13 16 17 22 33 142 | 111111 1 143 | 111110 0 144 | 111101 1 145 | 111100 0 146 | 111011 1 147 | 111010 0 148 | 111001 0 149 | 111000 0 150 | 110111 0 151 | 110110 0 152 | 110101 0 153 | 110100 0 154 | 110011 0 155 | 110010 0 156 | 110001 0 157 | 110000 0 158 | 101111 0 159 | 101110 0 160 | 101101 0 161 | 101100 0 162 | 101011 0 163 | 101010 0 164 | 101001 0 165 | 101000 0 166 | 100111 0 167 | 100110 0 168 | 100101 0 169 | 100100 0 170 | 100011 0 171 | 100010 0 172 | 100001 0 173 | 100000 0 174 | 011111 1 175 | 011110 0 176 | 011101 0 177 | 011100 0 178 | 011011 1 179 | 011010 0 180 | 011001 0 181 | 011000 0 182 | 010111 0 183 | 010110 0 184 | 010101 0 185 | 010100 0 186 | 010011 0 187 | 010010 0 188 | 010001 0 189 | 010000 0 190 | 001111 0 191 | 001110 0 192 | 001101 0 193 | 001100 0 194 | 001011 0 195 | 001010 0 196 | 001001 0 197 | 001000 0 198 | 000111 0 199 | 000110 0 200 | 000101 0 201 | 000100 0 202 | 000011 0 203 | 000010 0 204 | 000001 0 205 | 000000 0 206 | 207 | # 11 EC 208 | .n 11 1 13 209 | 1 1 210 | 0 0 211 | 212 | # 12 Th2I 213 | .n 12 1 18 214 | 1 1 215 | 0 0 216 | 217 | # 13 Bb 218 | .n 13 2 13 30 219 | 11 0 220 | 10 1 221 | 01 0 222 | 00 0 223 | 224 | # 14 PIC 225 | .n 14 4 9 10 11 32 226 | 1111 0 227 | 1110 0 228 | 1101 0 229 | 1100 0 230 | 1011 0 231 | 1010 0 232 | 1001 0 233 | 1000 0 234 | 0111 1 235 | 0110 1 236 | 0101 1 237 | 0100 1 238 | 0011 1 239 | 0010 1 240 | 0001 1 241 | 0000 0 242 | 243 | # 15 TrII 244 | .n 15 2 5 24 245 | 11 1 246 | 10 0 247 | 01 0 248 | 00 0 249 | 250 | # 16 MPI 251 | .n 16 3 1 13 14 252 | 111 1 253 | 110 1 254 | 101 0 255 | 100 0 256 | 011 1 257 | 010 0 258 | 001 0 259 | 000 0 260 | 261 | # 17 C 262 | .n 17 4 4 13 20 22 263 | 1111 1 264 | 1110 0 265 | 1101 1 266 | 1100 1 267 | 1011 1 268 | 1010 0 269 | 1001 1 270 | 1000 0 271 | 0111 0 272 | 0110 0 273 | 0101 1 274 | 0100 1 275 | 0011 0 276 | 0010 0 277 | 0001 0 278 | 0000 0 279 | 280 | # 18 Th2II 281 | .n 18 3 5 21 24 282 | 111 0 283 | 110 0 284 | 101 1 285 | 100 0 286 | 011 0 287 | 010 0 288 | 001 0 289 | 000 0 290 | 291 | # 19 TrI 292 | .n 19 1 15 293 | 1 1 294 | 0 0 295 | 296 | # 20 Oag 297 | .n 20 1 13 298 | 1 1 299 | 0 0 300 | 301 | # 21 IL12II 302 | .n 21 3 5 24 29 303 | 111 0 304 | 110 1 305 | 101 0 306 | 100 0 307 | 011 0 308 | 010 0 309 | 001 0 310 | 000 0 311 | 312 | # 22 AgAb 313 | .n 22 3 2 4 13 314 | 111 1 315 | 110 0 316 | 101 1 317 | 100 0 318 | 011 1 319 | 010 0 320 | 001 0 321 | 000 0 322 | 323 | # 23 DCI 324 | .n 23 3 1 13 14 325 | 111 1 326 | 110 1 327 | 101 0 328 | 100 0 329 | 011 1 330 | 010 0 331 | 001 0 332 | 000 0 333 | 334 | # 24 DCII 335 | .n 24 1 23 336 | 1 1 337 | 0 0 338 | 339 | # 25 IFNgII 340 | .n 25 1 1 341 | 1 1 342 | 0 0 343 | 344 | # 26 TTSSI 345 | .n 26 3 2 4 13 346 | 111 0 347 | 110 0 348 | 101 0 349 | 100 0 350 | 011 0 351 | 010 0 352 | 001 1 353 | 000 0 354 | 355 | # 27 BC 356 | .n 27 2 5 27 357 | 11 1 358 | 10 1 359 | 01 1 360 | 00 0 361 | 362 | # 28 NE 363 | .n 28 1 14 364 | 1 1 365 | 0 0 366 | 367 | # 29 IL4II 368 | .n 29 5 5 18 21 24 25 369 | 11111 0 370 | 11110 0 371 | 11101 0 372 | 11100 0 373 | 11011 0 374 | 11010 1 375 | 11001 0 376 | 11000 1 377 | 10111 0 378 | 10110 0 379 | 10101 0 380 | 10100 0 381 | 10011 0 382 | 10010 1 383 | 10001 0 384 | 10000 0 385 | 01111 0 386 | 01110 0 387 | 01101 0 388 | 01100 0 389 | 01011 0 390 | 01010 1 391 | 01001 0 392 | 01000 1 393 | 00111 0 394 | 00110 0 395 | 00101 0 396 | 00100 0 397 | 00011 0 398 | 00010 0 399 | 00001 0 400 | 00000 0 401 | 402 | # 30 PH 403 | .n 30 2 10 13 404 | 11 1 405 | 10 0 406 | 01 0 407 | 00 0 408 | 409 | # 31 IL12I 410 | .n 31 3 5 24 29 411 | 111 0 412 | 110 1 413 | 101 0 414 | 100 0 415 | 011 0 416 | 010 0 417 | 001 0 418 | 000 0 419 | 420 | # 32 DP 421 | .n 32 2 26 28 422 | 11 1 423 | 10 0 424 | 01 0 425 | 00 0 426 | 427 | # 33 Th1I 428 | .n 33 1 8 429 | 1 1 430 | 0 0 431 | 432 | .e End of file 433 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Budding Yeast Cell Cycle 2009.txt: -------------------------------------------------------------------------------- 1 | .v 18 2 | 3 | .l 1 SMBF 4 | .l 2 Cln2 5 | .l 3 S 6 | .l 4 Cdh1 7 | .l 5 CD 8 | .l 6 SFF 9 | .l 7 Clb2 10 | .l 8 Swi5 11 | .l 9 Cln3 12 | .l 10 B 13 | .l 11 FEAR 14 | .l 12 Clb5 15 | .l 13 M 16 | .l 14 Cdc20 17 | .l 15 MEN 18 | .l 16 CKI 19 | .l 17 Yhp1 20 | .l 18 Cdc14 21 | 22 | # 1 SMBF 23 | .n 1 4 1 2 7 9 24 | 1111 0 25 | 1110 0 26 | 1101 1 27 | 1100 1 28 | 1011 0 29 | 1010 0 30 | 1001 1 31 | 1000 1 32 | 0111 0 33 | 0110 0 34 | 0101 1 35 | 0100 1 36 | 0011 0 37 | 0010 0 38 | 0001 1 39 | 0000 0 40 | 41 | # 2 Cln2 42 | .n 2 1 1 43 | 1 1 44 | 0 0 45 | 46 | # 3 S 47 | .n 3 4 3 5 7 12 48 | 1111 0 49 | 1110 0 50 | 1101 0 51 | 1100 0 52 | 1011 1 53 | 1010 1 54 | 1001 1 55 | 1000 1 56 | 0111 0 57 | 0110 0 58 | 0101 0 59 | 0100 0 60 | 0011 1 61 | 0010 1 62 | 0001 1 63 | 0000 0 64 | 65 | # 4 Cdh1 66 | .n 4 4 2 7 12 18 67 | 1111 1 68 | 1110 0 69 | 1101 1 70 | 1100 0 71 | 1011 1 72 | 1010 0 73 | 1001 1 74 | 1000 0 75 | 0111 1 76 | 0110 0 77 | 0101 1 78 | 0100 0 79 | 0011 1 80 | 0010 0 81 | 0001 1 82 | 0000 1 83 | 84 | # 5 CD 85 | .n 5 4 5 11 13 18 86 | 1111 0 87 | 1110 0 88 | 1101 0 89 | 1100 0 90 | 1011 0 91 | 1010 0 92 | 1001 0 93 | 1000 0 94 | 0111 1 95 | 0110 0 96 | 0101 0 97 | 0100 0 98 | 0011 0 99 | 0010 0 100 | 0001 0 101 | 0000 0 102 | 103 | # 6 SFF 104 | .n 6 6 4 6 7 10 14 16 105 | 111111 1 106 | 111110 1 107 | 111101 1 108 | 111100 1 109 | 111011 1 110 | 111010 1 111 | 111001 1 112 | 111000 1 113 | 110111 0 114 | 110110 0 115 | 110101 0 116 | 110100 1 117 | 110011 0 118 | 110010 0 119 | 110001 0 120 | 110000 0 121 | 101111 0 122 | 101110 0 123 | 101101 0 124 | 101100 1 125 | 101011 0 126 | 101010 0 127 | 101001 0 128 | 101000 0 129 | 100111 0 130 | 100110 0 131 | 100101 0 132 | 100100 1 133 | 100011 0 134 | 100010 0 135 | 100001 0 136 | 100000 0 137 | 011111 1 138 | 011110 1 139 | 011101 1 140 | 011100 1 141 | 011011 1 142 | 011010 1 143 | 011001 1 144 | 011000 1 145 | 010111 0 146 | 010110 1 147 | 010101 0 148 | 010100 1 149 | 010011 0 150 | 010010 0 151 | 010001 0 152 | 010000 0 153 | 001111 0 154 | 001110 1 155 | 001101 0 156 | 001100 1 157 | 001011 0 158 | 001010 0 159 | 001001 0 160 | 001000 0 161 | 000111 0 162 | 000110 1 163 | 000101 0 164 | 000100 1 165 | 000011 0 166 | 000010 0 167 | 000001 0 168 | 000000 0 169 | 170 | # 7 Clb2 171 | .n 7 6 4 6 7 10 14 16 172 | 111111 0 173 | 111110 0 174 | 111101 0 175 | 111100 1 176 | 111011 0 177 | 111010 0 178 | 111001 0 179 | 111000 1 180 | 110111 0 181 | 110110 0 182 | 110101 0 183 | 110100 1 184 | 110011 0 185 | 110010 0 186 | 110001 0 187 | 110000 0 188 | 101111 0 189 | 101110 0 190 | 101101 0 191 | 101100 1 192 | 101011 0 193 | 101010 0 194 | 101001 0 195 | 101000 0 196 | 100111 0 197 | 100110 0 198 | 100101 0 199 | 100100 1 200 | 100011 0 201 | 100010 0 202 | 100001 0 203 | 100000 0 204 | 011111 0 205 | 011110 1 206 | 011101 0 207 | 011100 1 208 | 011011 0 209 | 011010 1 210 | 011001 0 211 | 011000 1 212 | 010111 0 213 | 010110 1 214 | 010101 0 215 | 010100 1 216 | 010011 0 217 | 010010 0 218 | 010001 0 219 | 010000 0 220 | 001111 0 221 | 001110 1 222 | 001101 0 223 | 001100 1 224 | 001011 0 225 | 001010 0 226 | 001001 0 227 | 001000 0 228 | 000111 0 229 | 000110 1 230 | 000101 0 231 | 000100 1 232 | 000011 0 233 | 000010 0 234 | 000001 0 235 | 000000 0 236 | 237 | # 8 Swi5 238 | .n 8 3 6 7 18 239 | 111 1 240 | 110 0 241 | 101 1 242 | 100 1 243 | 011 0 244 | 010 0 245 | 001 0 246 | 000 0 247 | 248 | # 9 Cln3 249 | .n 9 1 17 250 | 1 0 251 | 0 1 252 | 253 | # 10 B 254 | .n 10 4 2 5 10 12 255 | 1111 0 256 | 1110 0 257 | 1101 0 258 | 1100 0 259 | 1011 1 260 | 1010 1 261 | 1001 1 262 | 1000 1 263 | 0111 0 264 | 0110 0 265 | 0101 0 266 | 0100 0 267 | 0011 1 268 | 0010 1 269 | 0001 1 270 | 0000 0 271 | 272 | # 11 FEAR 273 | .n 11 1 14 274 | 1 1 275 | 0 0 276 | 277 | # 12 Clb5 278 | .n 12 3 1 14 16 279 | 111 0 280 | 110 0 281 | 101 1 282 | 100 1 283 | 011 0 284 | 010 0 285 | 001 0 286 | 000 0 287 | 288 | # 13 M 289 | .n 13 4 3 5 7 13 290 | 1111 0 291 | 1110 0 292 | 1101 0 293 | 1100 0 294 | 1011 1 295 | 1010 1 296 | 1001 1 297 | 1000 0 298 | 0111 0 299 | 0110 0 300 | 0101 0 301 | 0100 0 302 | 0011 1 303 | 0010 0 304 | 0001 1 305 | 0000 0 306 | 307 | # 14 Cdc20 308 | .n 14 3 6 7 13 309 | 111 1 310 | 110 0 311 | 101 0 312 | 100 0 313 | 011 0 314 | 010 0 315 | 001 0 316 | 000 0 317 | 318 | # 15 MEN 319 | .n 15 2 7 11 320 | 11 1 321 | 10 0 322 | 01 0 323 | 00 0 324 | 325 | # 16 CKI 326 | .n 16 6 2 7 8 12 16 18 327 | 111111 1 328 | 111110 0 329 | 111101 1 330 | 111100 0 331 | 111011 1 332 | 111010 0 333 | 111001 1 334 | 111000 0 335 | 110111 0 336 | 110110 0 337 | 110101 0 338 | 110100 0 339 | 110011 0 340 | 110010 0 341 | 110001 0 342 | 110000 0 343 | 101111 1 344 | 101110 0 345 | 101101 1 346 | 101100 0 347 | 101011 1 348 | 101010 0 349 | 101001 1 350 | 101000 0 351 | 100111 0 352 | 100110 0 353 | 100101 0 354 | 100100 0 355 | 100011 0 356 | 100010 0 357 | 100001 0 358 | 100000 0 359 | 011111 1 360 | 011110 0 361 | 011101 1 362 | 011100 0 363 | 011011 1 364 | 011010 0 365 | 011001 1 366 | 011000 0 367 | 010111 0 368 | 010110 0 369 | 010101 0 370 | 010100 0 371 | 010011 0 372 | 010010 0 373 | 010001 0 374 | 010000 0 375 | 001111 1 376 | 001110 0 377 | 001101 1 378 | 001100 0 379 | 001011 1 380 | 001010 1 381 | 001001 1 382 | 001000 1 383 | 000111 0 384 | 000110 0 385 | 000101 0 386 | 000100 0 387 | 000011 1 388 | 000010 1 389 | 000001 0 390 | 000000 0 391 | 392 | # 17 Yhp1 393 | .n 17 1 1 394 | 1 1 395 | 0 0 396 | 397 | # 18 Cdc14 398 | .n 18 2 11 15 399 | 11 1 400 | 10 0 401 | 01 0 402 | 00 0 403 | 404 | .e End of file 405 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Budding Yeast Cell Cycle.txt: -------------------------------------------------------------------------------- 1 | .v 20 2 | 3 | .l 1 SMBF 4 | .l 2 Sic1 5 | .l 3 Whi5 6 | .l 4 Clb2 7 | .l 5 Swe1 8 | .l 6 FEAR 9 | .l 7 Swi5 10 | .l 8 SFF 11 | .l 9 Cln2 12 | .l 10 Yhp1 13 | .l 11 Clb5 14 | .l 12 Cln3 15 | .l 13 Cdc20 16 | .l 14 Cdc14 17 | .l 15 MEN 18 | .l 16 Cdh1 19 | .l 17 SpindleCP 20 | .l 18 BuddingCP 21 | .l 19 Size 22 | .l 20 Start 23 | 24 | # 1 SMBF 25 | .n 1 2 3 4 26 | 11 0 27 | 10 0 28 | 01 0 29 | 00 1 30 | 31 | # 2 Sic1 32 | .n 2 6 2 4 7 9 11 14 33 | 111111 1 34 | 111110 0 35 | 111101 1 36 | 111100 0 37 | 111011 1 38 | 111010 0 39 | 111001 1 40 | 111000 0 41 | 110111 1 42 | 110110 0 43 | 110101 1 44 | 110100 0 45 | 110011 1 46 | 110010 0 47 | 110001 1 48 | 110000 0 49 | 101111 1 50 | 101110 0 51 | 101101 1 52 | 101100 0 53 | 101011 1 54 | 101010 0 55 | 101001 1 56 | 101000 1 57 | 100111 1 58 | 100110 0 59 | 100101 1 60 | 100100 0 61 | 100011 1 62 | 100010 0 63 | 100001 1 64 | 100000 1 65 | 011111 1 66 | 011110 0 67 | 011101 1 68 | 011100 0 69 | 011011 1 70 | 011010 0 71 | 011001 1 72 | 011000 0 73 | 010111 0 74 | 010110 0 75 | 010101 0 76 | 010100 0 77 | 010011 0 78 | 010010 0 79 | 010001 0 80 | 010000 0 81 | 001111 1 82 | 001110 0 83 | 001101 1 84 | 001100 0 85 | 001011 1 86 | 001010 0 87 | 001001 1 88 | 001000 1 89 | 000111 0 90 | 000110 0 91 | 000101 0 92 | 000100 0 93 | 000011 0 94 | 000010 0 95 | 000001 0 96 | 000000 1 97 | 98 | # 3 Whi5 99 | .n 3 3 9 12 20 100 | 111 0 101 | 110 1 102 | 101 0 103 | 100 1 104 | 011 0 105 | 010 1 106 | 001 1 107 | 000 1 108 | 109 | # 4 Clb2 110 | .n 4 5 2 5 8 13 16 111 | 11111 0 112 | 11110 0 113 | 11101 0 114 | 11100 0 115 | 11011 0 116 | 11010 0 117 | 11001 0 118 | 11000 0 119 | 10111 0 120 | 10110 1 121 | 10101 1 122 | 10100 1 123 | 10011 0 124 | 10010 0 125 | 10001 0 126 | 10000 0 127 | 01111 0 128 | 01110 0 129 | 01101 0 130 | 01100 0 131 | 01011 0 132 | 01010 0 133 | 01001 0 134 | 01000 0 135 | 00111 0 136 | 00110 1 137 | 00101 1 138 | 00100 1 139 | 00011 0 140 | 00010 0 141 | 00001 0 142 | 00000 1 143 | 144 | # 5 Swe1 145 | .n 5 1 18 146 | 1 0 147 | 0 1 148 | 149 | # 6 FEAR 150 | .n 6 1 13 151 | 1 1 152 | 0 0 153 | 154 | # 7 Swi5 155 | .n 7 4 4 7 8 14 156 | 1111 0 157 | 1110 0 158 | 1101 0 159 | 1100 0 160 | 1011 0 161 | 1010 0 162 | 1001 0 163 | 1000 0 164 | 0111 0 165 | 0110 0 166 | 0101 0 167 | 0100 0 168 | 0011 1 169 | 0010 0 170 | 0001 0 171 | 0000 0 172 | 173 | # 8 SFF 174 | .n 8 1 4 175 | 1 1 176 | 0 0 177 | 178 | # 9 Cln2 179 | .n 9 2 1 20 180 | 11 1 181 | 10 0 182 | 01 0 183 | 00 0 184 | 185 | # 10 Yhp1 186 | .n 10 1 1 187 | 1 1 188 | 0 0 189 | 190 | # 11 Clb5 191 | .n 11 3 1 2 13 192 | 111 0 193 | 110 0 194 | 101 0 195 | 100 1 196 | 011 0 197 | 010 0 198 | 001 0 199 | 000 0 200 | 201 | # 12 Cln3 202 | .n 12 2 10 19 203 | 11 0 204 | 10 0 205 | 01 1 206 | 00 0 207 | 208 | # 13 Cdc20 209 | .n 13 3 4 8 17 210 | 111 1 211 | 110 0 212 | 101 0 213 | 100 0 214 | 011 0 215 | 010 0 216 | 001 0 217 | 000 0 218 | 219 | # 14 Cdc14 220 | .n 14 2 6 15 221 | 11 1 222 | 10 0 223 | 01 0 224 | 00 0 225 | 226 | # 15 MEN 227 | .n 15 2 4 6 228 | 11 1 229 | 10 0 230 | 01 0 231 | 00 0 232 | 233 | # 16 Cdh1 234 | .n 16 4 4 9 11 14 235 | 1111 1 236 | 1110 0 237 | 1101 1 238 | 1100 0 239 | 1011 1 240 | 1010 0 241 | 1001 1 242 | 1000 0 243 | 0111 1 244 | 0110 0 245 | 0101 1 246 | 0100 0 247 | 0011 1 248 | 0010 0 249 | 0001 1 250 | 0000 1 251 | 252 | # 17 SpindleCP 253 | .n 17 0 254 | 255 | # 18 BuddingCP 256 | .n 18 0 257 | 258 | # 19 Size 259 | .n 19 0 260 | 261 | # 20 Start 262 | .n 20 0 263 | 264 | .e End of file 265 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Cardiac development.txt: -------------------------------------------------------------------------------- 1 | .v 15 2 | 3 | .l 1 Tbx1 4 | .l 2 Dkk1 5 | .l 3 GATAs 6 | .l 4 exogen_CanWnt_I 7 | .l 5 canWnt 8 | .l 6 Fgf8 9 | .l 7 Nkx2_5 10 | .l 8 Bmp2 11 | .l 9 exogen_canWnt_II 12 | .l 10 exogen_BMP2_II 13 | .l 11 Mesp1 14 | .l 12 Isl1 15 | .l 13 Foxc1_2 16 | .l 14 Tbx5 17 | .l 15 exogen_BMP2_I 18 | 19 | # 1 Tbx1 20 | .n 1 1 13 21 | 1 1 22 | 0 0 23 | 24 | # 2 Dkk1 25 | .n 2 3 5 10 11 26 | 111 1 27 | 110 0 28 | 101 1 29 | 100 1 30 | 011 1 31 | 010 0 32 | 001 1 33 | 000 0 34 | 35 | # 3 GATAs 36 | .n 3 3 7 11 14 37 | 111 1 38 | 110 1 39 | 101 1 40 | 100 1 41 | 011 1 42 | 010 1 43 | 001 1 44 | 000 0 45 | 46 | # 4 exogen_CanWnt_I 47 | .n 4 1 4 48 | 1 1 49 | 0 0 50 | 51 | # 5 canWnt 52 | .n 5 1 9 53 | 1 1 54 | 0 0 55 | 56 | # 6 Fgf8 57 | .n 6 3 1 11 13 58 | 111 0 59 | 110 0 60 | 101 1 61 | 100 1 62 | 011 0 63 | 010 0 64 | 001 1 65 | 000 0 66 | 67 | # 7 Nkx2_5 68 | .n 7 7 1 2 3 8 11 12 14 69 | 1111111 1 70 | 1111110 1 71 | 1111101 1 72 | 1111100 1 73 | 1111011 1 74 | 1111010 1 75 | 1111001 1 76 | 1111000 1 77 | 1110111 1 78 | 1110110 1 79 | 1110101 1 80 | 1110100 1 81 | 1110011 1 82 | 1110010 1 83 | 1110001 1 84 | 1110000 1 85 | 1101111 1 86 | 1101110 1 87 | 1101101 1 88 | 1101100 1 89 | 1101011 1 90 | 1101010 1 91 | 1101001 1 92 | 1101000 1 93 | 1100111 1 94 | 1100110 1 95 | 1100101 1 96 | 1100100 1 97 | 1100011 1 98 | 1100010 1 99 | 1100001 1 100 | 1100000 1 101 | 1011111 1 102 | 1011110 1 103 | 1011101 1 104 | 1011100 1 105 | 1011011 1 106 | 1011010 1 107 | 1011001 1 108 | 1011000 1 109 | 1010111 1 110 | 1010110 1 111 | 1010101 1 112 | 1010100 1 113 | 1010011 1 114 | 1010010 1 115 | 1010001 1 116 | 1010000 1 117 | 1001111 1 118 | 1001110 1 119 | 1001101 1 120 | 1001100 1 121 | 1001011 1 122 | 1001010 1 123 | 1001001 1 124 | 1001000 1 125 | 1000111 1 126 | 1000110 1 127 | 1000101 1 128 | 1000100 1 129 | 1000011 1 130 | 1000010 1 131 | 1000001 1 132 | 1000000 1 133 | 0111111 1 134 | 0111110 1 135 | 0111101 1 136 | 0111100 1 137 | 0111011 1 138 | 0111010 1 139 | 0111001 1 140 | 0111000 1 141 | 0110111 1 142 | 0110110 1 143 | 0110101 1 144 | 0110100 1 145 | 0110011 1 146 | 0110010 1 147 | 0110001 1 148 | 0110000 0 149 | 0101111 1 150 | 0101110 1 151 | 0101101 1 152 | 0101100 1 153 | 0101011 1 154 | 0101010 0 155 | 0101001 1 156 | 0101000 0 157 | 0100111 1 158 | 0100110 1 159 | 0100101 1 160 | 0100100 1 161 | 0100011 1 162 | 0100010 0 163 | 0100001 1 164 | 0100000 0 165 | 0011111 1 166 | 0011110 1 167 | 0011101 1 168 | 0011100 1 169 | 0011011 1 170 | 0011010 1 171 | 0011001 1 172 | 0011000 1 173 | 0010111 1 174 | 0010110 1 175 | 0010101 1 176 | 0010100 0 177 | 0010011 1 178 | 0010010 1 179 | 0010001 1 180 | 0010000 0 181 | 0001111 1 182 | 0001110 0 183 | 0001101 1 184 | 0001100 0 185 | 0001011 1 186 | 0001010 0 187 | 0001001 1 188 | 0001000 0 189 | 0000111 1 190 | 0000110 0 191 | 0000101 1 192 | 0000100 0 193 | 0000011 1 194 | 0000010 0 195 | 0000001 1 196 | 0000000 0 197 | 198 | # 8 Bmp2 199 | .n 8 2 5 10 200 | 11 0 201 | 10 0 202 | 01 1 203 | 00 0 204 | 205 | # 9 exogen_canWnt_II 206 | .n 9 1 4 207 | 1 1 208 | 0 0 209 | 210 | # 10 exogen_BMP2_II 211 | .n 10 1 15 212 | 1 1 213 | 0 0 214 | 215 | # 11 Mesp1 216 | .n 11 2 5 10 217 | 11 0 218 | 10 1 219 | 01 0 220 | 00 0 221 | 222 | # 12 Isl1 223 | .n 12 5 1 5 6 9 11 224 | 11111 1 225 | 11110 1 226 | 11101 1 227 | 11100 1 228 | 11011 1 229 | 11010 1 230 | 11001 1 231 | 11000 1 232 | 10111 1 233 | 10110 1 234 | 10101 1 235 | 10100 1 236 | 10011 1 237 | 10010 1 238 | 10001 1 239 | 10000 1 240 | 01111 1 241 | 01110 1 242 | 01101 1 243 | 01100 1 244 | 01011 1 245 | 01010 1 246 | 01001 1 247 | 01000 0 248 | 00111 1 249 | 00110 1 250 | 00101 1 251 | 00100 1 252 | 00011 1 253 | 00010 0 254 | 00001 1 255 | 00000 0 256 | 257 | # 13 Foxc1_2 258 | .n 13 2 5 9 259 | 11 1 260 | 10 0 261 | 01 0 262 | 00 0 263 | 264 | # 14 Tbx5 265 | .n 14 6 1 2 5 7 11 14 266 | 111111 0 267 | 111110 0 268 | 111101 0 269 | 111100 0 270 | 111011 0 271 | 111010 0 272 | 111001 0 273 | 111000 0 274 | 110111 0 275 | 110110 0 276 | 110101 0 277 | 110100 0 278 | 110011 0 279 | 110010 0 280 | 110001 0 281 | 110000 0 282 | 101111 0 283 | 101110 0 284 | 101101 0 285 | 101100 0 286 | 101011 0 287 | 101010 0 288 | 101001 0 289 | 101000 0 290 | 100111 0 291 | 100110 0 292 | 100101 0 293 | 100100 0 294 | 100011 0 295 | 100010 0 296 | 100001 0 297 | 100000 0 298 | 011111 0 299 | 011110 0 300 | 011101 0 301 | 011100 0 302 | 011011 0 303 | 011010 0 304 | 011001 0 305 | 011000 0 306 | 010111 1 307 | 010110 1 308 | 010101 1 309 | 010100 0 310 | 010011 1 311 | 010010 1 312 | 010001 1 313 | 010000 0 314 | 001111 0 315 | 001110 0 316 | 001101 0 317 | 001100 0 318 | 001011 0 319 | 001010 0 320 | 001001 0 321 | 001000 0 322 | 000111 1 323 | 000110 1 324 | 000101 1 325 | 000100 1 326 | 000011 1 327 | 000010 1 328 | 000001 1 329 | 000000 0 330 | 331 | # 15 exogen_BMP2_I 332 | .n 15 0 333 | 334 | .e End of file 335 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Cell Cycle Transcription by Coupled CDK and Network Oscillators.txt: -------------------------------------------------------------------------------- 1 | .v 9 2 | 3 | .l 1 ACE2 4 | .l 2 YHP1 5 | .l 3 YOX1 6 | .l 4 MBF 7 | .l 5 SBF 8 | .l 6 SWI5 9 | .l 7 HCM1 10 | .l 8 SFF 11 | .l 9 CLN3 12 | 13 | # 1 ACE2 14 | .n 1 1 8 15 | 1 1 16 | 0 0 17 | 18 | # 2 YHP1 19 | .n 2 2 4 5 20 | 11 1 21 | 10 1 22 | 01 1 23 | 00 0 24 | 25 | # 3 YOX1 26 | .n 3 2 4 5 27 | 11 1 28 | 10 0 29 | 01 0 30 | 00 0 31 | 32 | # 4 MBF 33 | .n 4 1 9 34 | 1 1 35 | 0 0 36 | 37 | # 5 SBF 38 | .n 5 4 2 3 4 9 39 | 1111 0 40 | 1110 0 41 | 1101 0 42 | 1100 0 43 | 1011 0 44 | 1010 0 45 | 1001 0 46 | 1000 0 47 | 0111 0 48 | 0110 0 49 | 0101 0 50 | 0100 0 51 | 0011 1 52 | 0010 1 53 | 0001 1 54 | 0000 0 55 | 56 | # 6 SWI5 57 | .n 6 1 8 58 | 1 1 59 | 0 0 60 | 61 | # 7 HCM1 62 | .n 7 2 4 5 63 | 11 1 64 | 10 0 65 | 01 0 66 | 00 0 67 | 68 | # 8 SFF 69 | .n 8 2 5 7 70 | 11 1 71 | 10 0 72 | 01 0 73 | 00 0 74 | 75 | # 9 CLN3 76 | .n 9 4 1 2 3 6 77 | 1111 0 78 | 1110 0 79 | 1101 0 80 | 1100 0 81 | 1011 0 82 | 1010 0 83 | 1001 1 84 | 1000 0 85 | 0111 0 86 | 0110 0 87 | 0101 0 88 | 0100 0 89 | 0011 0 90 | 0010 0 91 | 0001 0 92 | 0000 0 93 | 94 | .e End of file 95 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Cholesterol Regulatory Pathway.txt: -------------------------------------------------------------------------------- 1 | .v 34 2 | 3 | .l 1 HMG_CoA_Reductase_RNA 4 | .l 2 Geranyl_pyrophosphate 5 | .l 3 Dimethyl_allyl_pyrophosphate 6 | .l 4 Acetyl_CoA 7 | .l 5 HMG_CoA_Synthase 8 | .l 6 Squaline 9 | .l 7 Cholesterol 10 | .l 8 HMG_CoA_Reductase_gene 11 | .l 9 HMG_CoA 12 | .l 10 Lanosterol 13 | .l 11 pSREBP 14 | .l 12 FPP_Synthase 15 | .l 13 Desmosterol 16 | .l 14 Cyp51 17 | .l 15 Isopentenyl_pyrophosphate 18 | .l 16 Septdehydrocholesterol 19 | .l 17 Acetyl_CoA_acetyltransferase 20 | .l 18 Mevalonyl_pyrophosphate 21 | .l 19 HMG_CoA_Synthase_RNA 22 | .l 20 mSREBP 23 | .l 21 Acetyl_CoA_acetyltransferase_RNA 24 | .l 22 Insig_SREBP_SCAP 25 | .l 23 Acetyl_CoA_acetyltransferase_gene 26 | .l 24 FPP_Synthase_RNA 27 | .l 25 FPP_Synthase_gene 28 | .l 26 Cyp51_gene 29 | .l 27 Statins 30 | .l 28 Mevalonic_Acid 31 | .l 29 SREBP_SCAP 32 | .l 30 HMG_CoA_Reductase 33 | .l 31 Acetoacetyl_CoA 34 | .l 32 Farnesyl_pyrophosphate 35 | .l 33 HMG_CoA_Synthase_gene 36 | .l 34 Cyp51_RNA 37 | 38 | # 1 HMG_CoA_Reductase_RNA 39 | .n 1 1 8 40 | 1 1 41 | 0 0 42 | 43 | # 2 Geranyl_pyrophosphate 44 | .n 2 2 3 15 45 | 11 1 46 | 10 1 47 | 01 1 48 | 00 0 49 | 50 | # 3 Dimethyl_allyl_pyrophosphate 51 | .n 3 1 15 52 | 1 1 53 | 0 0 54 | 55 | # 4 Acetyl_CoA 56 | .n 4 1 4 57 | 1 1 58 | 0 0 59 | 60 | # 5 HMG_CoA_Synthase 61 | .n 5 1 19 62 | 1 1 63 | 0 0 64 | 65 | # 6 Squaline 66 | .n 6 1 32 67 | 1 1 68 | 0 0 69 | 70 | # 7 Cholesterol 71 | .n 7 2 13 16 72 | 11 1 73 | 10 1 74 | 01 1 75 | 00 0 76 | 77 | # 8 HMG_CoA_Reductase_gene 78 | .n 8 1 20 79 | 1 1 80 | 0 0 81 | 82 | # 9 HMG_CoA 83 | .n 9 3 4 5 31 84 | 111 1 85 | 110 0 86 | 101 0 87 | 100 0 88 | 011 0 89 | 010 0 90 | 001 0 91 | 000 0 92 | 93 | # 10 Lanosterol 94 | .n 10 1 6 95 | 1 1 96 | 0 0 97 | 98 | # 11 pSREBP 99 | .n 11 1 29 100 | 1 1 101 | 0 0 102 | 103 | # 12 FPP_Synthase 104 | .n 12 1 24 105 | 1 1 106 | 0 0 107 | 108 | # 13 Desmosterol 109 | .n 13 1 10 110 | 1 1 111 | 0 0 112 | 113 | # 14 Cyp51 114 | .n 14 1 34 115 | 1 1 116 | 0 0 117 | 118 | # 15 Isopentenyl_pyrophosphate 119 | .n 15 1 18 120 | 1 1 121 | 0 0 122 | 123 | # 16 Septdehydrocholesterol 124 | .n 16 1 10 125 | 1 1 126 | 0 0 127 | 128 | # 17 Acetyl_CoA_acetyltransferase 129 | .n 17 1 21 130 | 1 1 131 | 0 0 132 | 133 | # 18 Mevalonyl_pyrophosphate 134 | .n 18 1 28 135 | 1 1 136 | 0 0 137 | 138 | # 19 HMG_CoA_Synthase_RNA 139 | .n 19 1 33 140 | 1 1 141 | 0 0 142 | 143 | # 20 mSREBP 144 | .n 20 1 11 145 | 1 1 146 | 0 0 147 | 148 | # 21 Acetyl_CoA_acetyltransferase_RNA 149 | .n 21 1 23 150 | 1 1 151 | 0 0 152 | 153 | # 22 Insig_SREBP_SCAP 154 | .n 22 1 7 155 | 1 0 156 | 0 1 157 | 158 | # 23 Acetyl_CoA_acetyltransferase_gene 159 | .n 23 1 20 160 | 1 1 161 | 0 0 162 | 163 | # 24 FPP_Synthase_RNA 164 | .n 24 1 25 165 | 1 1 166 | 0 0 167 | 168 | # 25 FPP_Synthase_gene 169 | .n 25 1 20 170 | 1 1 171 | 0 0 172 | 173 | # 26 Cyp51_gene 174 | .n 26 1 20 175 | 1 1 176 | 0 0 177 | 178 | # 27 Statins 179 | .n 27 1 27 180 | 1 1 181 | 0 0 182 | 183 | # 28 Mevalonic_Acid 184 | .n 28 2 9 30 185 | 11 1 186 | 10 0 187 | 01 0 188 | 00 0 189 | 190 | # 29 SREBP_SCAP 191 | .n 29 2 22 27 192 | 11 0 193 | 10 1 194 | 01 0 195 | 00 0 196 | 197 | # 30 HMG_CoA_Reductase 198 | .n 30 2 1 27 199 | 11 0 200 | 10 1 201 | 01 0 202 | 00 0 203 | 204 | # 31 Acetoacetyl_CoA 205 | .n 31 2 4 17 206 | 11 1 207 | 10 0 208 | 01 0 209 | 00 0 210 | 211 | # 32 Farnesyl_pyrophosphate 212 | .n 32 2 2 12 213 | 11 0 214 | 10 1 215 | 01 0 216 | 00 0 217 | 218 | # 33 HMG_CoA_Synthase_gene 219 | .n 33 1 20 220 | 1 1 221 | 0 0 222 | 223 | # 34 Cyp51_RNA 224 | .n 34 1 26 225 | 1 1 226 | 0 0 227 | 228 | .e End of file 229 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Cortical Area Development.txt: -------------------------------------------------------------------------------- 1 | .v 5 2 | 3 | .l 1 Emx2 4 | .l 2 Pax6 5 | .l 3 Fgf8 6 | .l 4 Coup_fti 7 | .l 5 Sp8 8 | 9 | # 1 Emx2 10 | .n 1 4 2 3 4 5 11 | 1111 0 12 | 1110 0 13 | 1101 0 14 | 1100 0 15 | 1011 0 16 | 1010 0 17 | 1001 0 18 | 1000 0 19 | 0111 0 20 | 0110 0 21 | 0101 0 22 | 0100 0 23 | 0011 0 24 | 0010 1 25 | 0001 0 26 | 0000 0 27 | 28 | # 2 Pax6 29 | .n 2 3 1 4 5 30 | 111 0 31 | 110 0 32 | 101 0 33 | 100 0 34 | 011 0 35 | 010 0 36 | 001 1 37 | 000 0 38 | 39 | # 3 Fgf8 40 | .n 3 3 1 3 5 41 | 111 0 42 | 110 0 43 | 101 0 44 | 100 0 45 | 011 1 46 | 010 0 47 | 001 0 48 | 000 0 49 | 50 | # 4 Coup_fti 51 | .n 4 2 3 5 52 | 11 0 53 | 10 0 54 | 01 0 55 | 00 1 56 | 57 | # 5 Sp8 58 | .n 5 2 1 3 59 | 11 0 60 | 10 0 61 | 01 1 62 | 00 0 63 | 64 | .e End of file 65 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Death Receptor Signaling.txt: -------------------------------------------------------------------------------- 1 | .v 28 2 | 3 | .l 1 CASP8 4 | .l 2 RIP1ub 5 | .l 3 DISC-TNF 6 | .l 4 BCL2 7 | .l 5 apoptosis 8 | .l 6 cIAP 9 | .l 7 RIP1k 10 | .l 8 DISC-FAS 11 | .l 9 MOMP 12 | .l 10 Cyt_c 13 | .l 11 MPT 14 | .l 12 SMAC 15 | .l 13 RIP1 16 | .l 14 CASP3 17 | .l 15 ATP 18 | .l 16 TNFR 19 | .l 17 survival 20 | .l 18 XIAP 21 | .l 19 ROS 22 | .l 20 BAX 23 | .l 21 apoptosome 24 | .l 22 cFLIP 25 | .l 23 IKK 26 | .l 24 NonACD 27 | .l 25 NFkB 28 | .l 26 FADD 29 | .l 27 TNF 30 | .l 28 FASL 31 | 32 | # 1 CASP8 33 | .n 1 4 3 8 14 22 34 | 1111 0 35 | 1110 1 36 | 1101 0 37 | 1100 1 38 | 1011 0 39 | 1010 1 40 | 1001 0 41 | 1000 1 42 | 0111 0 43 | 0110 1 44 | 0101 0 45 | 0100 1 46 | 0011 0 47 | 0010 1 48 | 0001 0 49 | 0000 0 50 | 51 | # 2 RIP1ub 52 | .n 2 2 6 13 53 | 11 1 54 | 10 0 55 | 01 0 56 | 00 0 57 | 58 | # 3 DISC-TNF 59 | .n 3 2 16 26 60 | 11 1 61 | 10 0 62 | 01 0 63 | 00 0 64 | 65 | # 4 BCL2 66 | .n 4 1 25 67 | 1 1 68 | 0 0 69 | 70 | # 5 apoptosis 71 | .n 5 1 14 72 | 1 1 73 | 0 0 74 | 75 | # 6 cIAP 76 | .n 6 3 6 12 25 77 | 111 0 78 | 110 0 79 | 101 1 80 | 100 1 81 | 011 0 82 | 010 0 83 | 001 1 84 | 000 0 85 | 86 | # 7 RIP1k 87 | .n 7 1 13 88 | 1 1 89 | 0 0 90 | 91 | # 8 DISC-FAS 92 | .n 8 2 26 28 93 | 11 1 94 | 10 0 95 | 01 0 96 | 00 0 97 | 98 | # 9 MOMP 99 | .n 9 2 11 20 100 | 11 1 101 | 10 1 102 | 01 1 103 | 00 0 104 | 105 | # 10 Cyt_c 106 | .n 10 1 9 107 | 1 1 108 | 0 0 109 | 110 | # 11 MPT 111 | .n 11 2 4 19 112 | 11 0 113 | 10 0 114 | 01 1 115 | 00 0 116 | 117 | # 12 SMAC 118 | .n 12 1 9 119 | 1 1 120 | 0 0 121 | 122 | # 13 RIP1 123 | .n 13 3 1 8 16 124 | 111 0 125 | 110 0 126 | 101 0 127 | 100 0 128 | 011 1 129 | 010 1 130 | 001 1 131 | 000 0 132 | 133 | # 14 CASP3 134 | .n 14 2 18 21 135 | 11 0 136 | 10 0 137 | 01 1 138 | 00 0 139 | 140 | # 15 ATP 141 | .n 15 1 11 142 | 1 0 143 | 0 1 144 | 145 | # 16 TNFR 146 | .n 16 1 27 147 | 1 1 148 | 0 0 149 | 150 | # 17 survival 151 | .n 17 1 25 152 | 1 1 153 | 0 0 154 | 155 | # 18 XIAP 156 | .n 18 2 12 25 157 | 11 0 158 | 10 0 159 | 01 1 160 | 00 0 161 | 162 | # 19 ROS 163 | .n 19 3 7 11 25 164 | 111 0 165 | 110 1 166 | 101 0 167 | 100 1 168 | 011 0 169 | 010 1 170 | 001 0 171 | 000 0 172 | 173 | # 20 BAX 174 | .n 20 2 1 4 175 | 11 0 176 | 10 1 177 | 01 0 178 | 00 0 179 | 180 | # 21 apoptosome 181 | .n 21 3 10 15 18 182 | 111 0 183 | 110 1 184 | 101 0 185 | 100 0 186 | 011 0 187 | 010 0 188 | 001 0 189 | 000 0 190 | 191 | # 22 cFLIP 192 | .n 22 1 25 193 | 1 1 194 | 0 0 195 | 196 | # 23 IKK 197 | .n 23 1 2 198 | 1 1 199 | 0 0 200 | 201 | # 24 NonACD 202 | .n 24 1 15 203 | 1 0 204 | 0 1 205 | 206 | # 25 NFkB 207 | .n 25 2 14 23 208 | 11 0 209 | 10 0 210 | 01 1 211 | 00 0 212 | 213 | # 26 FADD 214 | .n 26 0 215 | 216 | # 27 TNF 217 | .n 27 0 218 | 219 | # 28 FASL 220 | .n 28 0 221 | 222 | .e End of file 223 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/FGF pathway of Drosophila Signalling Pathways.txt: -------------------------------------------------------------------------------- 1 | .v 23 2 | 3 | .l 1 Btl 4 | .l 2 Drk 5 | .l 3 Dsor1 6 | .l 4 Htl 7 | .l 5 Rl 8 | .l 6 Aop 9 | .l 7 Stumps 10 | .l 8 Ras 11 | .l 9 Targets 12 | .l 10 Raf 13 | .l 11 PLCg 14 | .l 12 Sos 15 | .l 13 Pnt 16 | .l 14 Gap 17 | .l 15 Ths 18 | .l 16 Sty 19 | .l 17 Cnk 20 | .l 18 Msk 21 | .l 19 Src42 22 | .l 20 Pyr 23 | .l 21 Csw 24 | .l 22 Bnl 25 | .l 23 Ksr 26 | 27 | # 1 Btl 28 | .n 1 1 22 29 | 1 1 30 | 0 0 31 | 32 | # 2 Drk 33 | .n 2 2 7 21 34 | 11 1 35 | 10 0 36 | 01 0 37 | 00 0 38 | 39 | # 3 Dsor1 40 | .n 3 1 10 41 | 1 1 42 | 0 0 43 | 44 | # 4 Htl 45 | .n 4 2 15 20 46 | 11 1 47 | 10 1 48 | 01 1 49 | 00 0 50 | 51 | # 5 Rl 52 | .n 5 2 3 18 53 | 11 1 54 | 10 0 55 | 01 0 56 | 00 0 57 | 58 | # 6 Aop 59 | .n 6 1 5 60 | 1 0 61 | 0 1 62 | 63 | # 7 Stumps 64 | .n 7 2 1 4 65 | 11 1 66 | 10 1 67 | 01 1 68 | 00 0 69 | 70 | # 8 Ras 71 | .n 8 3 12 14 16 72 | 111 1 73 | 110 1 74 | 101 1 75 | 100 1 76 | 011 0 77 | 010 0 78 | 001 0 79 | 000 0 80 | 81 | # 9 Targets 82 | .n 9 2 6 13 83 | 11 0 84 | 10 0 85 | 01 1 86 | 00 0 87 | 88 | # 10 Raf 89 | .n 10 4 8 17 19 23 90 | 1111 1 91 | 1110 0 92 | 1101 0 93 | 1100 0 94 | 1011 0 95 | 1010 0 96 | 1001 0 97 | 1000 0 98 | 0111 0 99 | 0110 0 100 | 0101 0 101 | 0100 0 102 | 0011 0 103 | 0010 0 104 | 0001 0 105 | 0000 0 106 | 107 | # 11 PLCg 108 | .n 11 1 2 109 | 1 1 110 | 0 0 111 | 112 | # 12 Sos 113 | .n 12 1 2 114 | 1 1 115 | 0 0 116 | 117 | # 13 Pnt 118 | .n 13 1 5 119 | 1 1 120 | 0 0 121 | 122 | # 14 Gap 123 | .n 14 1 11 124 | 1 1 125 | 0 0 126 | 127 | # 15 Ths 128 | .n 15 0 129 | 130 | # 16 Sty 131 | .n 16 0 132 | 133 | # 17 Cnk 134 | .n 17 0 135 | 136 | # 18 Msk 137 | .n 18 0 138 | 139 | # 19 Src42 140 | .n 19 0 141 | 142 | # 20 Pyr 143 | .n 20 0 144 | 145 | # 21 Csw 146 | .n 21 0 147 | 148 | # 22 Bnl 149 | .n 22 0 150 | 151 | # 23 Ksr 152 | .n 23 0 153 | 154 | .e End of file 155 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Guard Cell Abscisic Acid Signaling.txt: -------------------------------------------------------------------------------- 1 | .v 44 2 | 3 | .l 1 ROS 4 | .l 2 NOS 5 | .l 3 AGB1 6 | .l 4 KAP 7 | .l 5 cGMP 8 | .l 6 GPA1 9 | .l 7 AnionEM 10 | .l 8 PA 11 | .l 9 Ca2_c 12 | .l 10 S1P 13 | .l 11 pH 14 | .l 12 CIS 15 | .l 13 OST1 16 | .l 14 GC 17 | .l 15 ABI1 18 | .l 16 SphK 19 | .l 17 ROP2 20 | .l 18 NO 21 | .l 19 RCN1 22 | .l 20 Depolar 23 | .l 21 PEPC 24 | .l 22 cADPR 25 | .l 23 InsPK 26 | .l 24 Atrboh 27 | .l 25 Actin 28 | .l 26 CaIM 29 | .l 27 Malate 30 | .l 28 RAC1 31 | .l 29 InsP3 32 | .l 30 InsP6 33 | .l 31 KOUT 34 | .l 32 HTPase 35 | .l 33 PLC 36 | .l 34 ROP10 37 | .l 35 KEV 38 | .l 36 ADPRc 39 | .l 37 Ca2_ATPase 40 | .l 38 NIA12 41 | .l 39 Closure 42 | .l 40 PLD 43 | .l 41 ERA1 44 | .l 42 ABA 45 | .l 43 GCR1 46 | .l 44 ABH1 47 | 48 | # 1 ROS 49 | .n 1 1 24 50 | 1 1 51 | 0 0 52 | 53 | # 2 NOS 54 | .n 2 1 9 55 | 1 1 56 | 0 0 57 | 58 | # 3 AGB1 59 | .n 3 1 6 60 | 1 1 61 | 0 0 62 | 63 | # 4 KAP 64 | .n 4 3 9 11 20 65 | 111 0 66 | 110 0 67 | 101 1 68 | 100 0 69 | 011 1 70 | 010 0 71 | 001 1 72 | 000 0 73 | 74 | # 5 cGMP 75 | .n 5 1 14 76 | 1 1 77 | 0 0 78 | 79 | # 6 GPA1 80 | .n 6 3 3 10 43 81 | 111 1 82 | 110 1 83 | 101 0 84 | 100 1 85 | 011 0 86 | 010 0 87 | 001 0 88 | 000 0 89 | 90 | # 7 AnionEM 91 | .n 7 3 9 11 15 92 | 111 1 93 | 110 1 94 | 101 0 95 | 100 1 96 | 011 0 97 | 010 1 98 | 001 0 99 | 000 0 100 | 101 | # 8 PA 102 | .n 8 1 40 103 | 1 1 104 | 0 0 105 | 106 | # 9 Ca2_c 107 | .n 9 3 12 26 37 108 | 111 0 109 | 110 1 110 | 101 0 111 | 100 1 112 | 011 0 113 | 010 1 114 | 001 0 115 | 000 0 116 | 117 | # 10 S1P 118 | .n 10 1 16 119 | 1 1 120 | 0 0 121 | 122 | # 11 pH 123 | .n 11 1 42 124 | 1 1 125 | 0 0 126 | 127 | # 12 CIS 128 | .n 12 4 5 22 29 30 129 | 1111 1 130 | 1110 1 131 | 1101 1 132 | 1100 1 133 | 1011 1 134 | 1010 0 135 | 1001 0 136 | 1000 0 137 | 0111 1 138 | 0110 0 139 | 0101 0 140 | 0100 0 141 | 0011 1 142 | 0010 0 143 | 0001 0 144 | 0000 0 145 | 146 | # 13 OST1 147 | .n 13 1 42 148 | 1 1 149 | 0 0 150 | 151 | # 14 GC 152 | .n 14 1 18 153 | 1 1 154 | 0 0 155 | 156 | # 15 ABI1 157 | .n 15 3 1 8 11 158 | 111 0 159 | 110 0 160 | 101 0 161 | 100 0 162 | 011 0 163 | 010 0 164 | 001 1 165 | 000 0 166 | 167 | # 16 SphK 168 | .n 16 1 42 169 | 1 1 170 | 0 0 171 | 172 | # 17 ROP2 173 | .n 17 1 8 174 | 1 1 175 | 0 0 176 | 177 | # 18 NO 178 | .n 18 2 2 38 179 | 11 1 180 | 10 0 181 | 01 0 182 | 00 0 183 | 184 | # 19 RCN1 185 | .n 19 1 42 186 | 1 1 187 | 0 0 188 | 189 | # 20 Depolar 190 | .n 20 5 7 9 31 32 35 191 | 11111 1 192 | 11110 1 193 | 11101 1 194 | 11100 1 195 | 11011 1 196 | 11010 1 197 | 11001 1 198 | 11000 1 199 | 10111 1 200 | 10110 1 201 | 10101 1 202 | 10100 1 203 | 10011 1 204 | 10010 1 205 | 10001 1 206 | 10000 1 207 | 01111 1 208 | 01110 1 209 | 01101 1 210 | 01100 1 211 | 01011 1 212 | 01010 1 213 | 01001 1 214 | 01000 1 215 | 00111 1 216 | 00110 0 217 | 00101 1 218 | 00100 1 219 | 00011 1 220 | 00010 1 221 | 00001 1 222 | 00000 1 223 | 224 | # 21 PEPC 225 | .n 21 1 42 226 | 1 0 227 | 0 1 228 | 229 | # 22 cADPR 230 | .n 22 1 36 231 | 1 1 232 | 0 0 233 | 234 | # 23 InsPK 235 | .n 23 1 42 236 | 1 1 237 | 0 0 238 | 239 | # 24 Atrboh 240 | .n 24 4 11 13 15 17 241 | 1111 0 242 | 1110 0 243 | 1101 1 244 | 1100 0 245 | 1011 0 246 | 1010 0 247 | 1001 0 248 | 1000 0 249 | 0111 0 250 | 0110 0 251 | 0101 0 252 | 0100 0 253 | 0011 0 254 | 0010 0 255 | 0001 0 256 | 0000 0 257 | 258 | # 25 Actin 259 | .n 25 2 9 28 260 | 11 1 261 | 10 1 262 | 01 0 263 | 00 1 264 | 265 | # 26 CaIM 266 | .n 26 4 1 20 41 44 267 | 1111 0 268 | 1110 0 269 | 1101 0 270 | 1100 0 271 | 1011 1 272 | 1010 1 273 | 1001 1 274 | 1000 1 275 | 0111 0 276 | 0110 0 277 | 0101 0 278 | 0100 0 279 | 0011 0 280 | 0010 1 281 | 0001 1 282 | 0000 1 283 | 284 | # 27 Malate 285 | .n 27 3 7 21 42 286 | 111 0 287 | 110 0 288 | 101 0 289 | 100 0 290 | 011 0 291 | 010 1 292 | 001 0 293 | 000 0 294 | 295 | # 28 RAC1 296 | .n 28 2 15 42 297 | 11 0 298 | 10 0 299 | 01 0 300 | 00 1 301 | 302 | # 29 InsP3 303 | .n 29 1 33 304 | 1 1 305 | 0 0 306 | 307 | # 30 InsP6 308 | .n 30 1 23 309 | 1 1 310 | 0 0 311 | 312 | # 31 KOUT 313 | .n 31 4 1 11 18 20 314 | 1111 1 315 | 1110 0 316 | 1101 1 317 | 1100 0 318 | 1011 0 319 | 1010 0 320 | 1001 1 321 | 1000 0 322 | 0111 1 323 | 0110 0 324 | 0101 1 325 | 0100 0 326 | 0011 1 327 | 0010 0 328 | 0001 1 329 | 0000 0 330 | 331 | # 32 HTPase 332 | .n 32 3 1 9 11 333 | 111 0 334 | 110 0 335 | 101 0 336 | 100 0 337 | 011 0 338 | 010 0 339 | 001 0 340 | 000 1 341 | 342 | # 33 PLC 343 | .n 33 2 9 42 344 | 11 1 345 | 10 0 346 | 01 0 347 | 00 0 348 | 349 | # 34 ROP10 350 | .n 34 1 41 351 | 1 1 352 | 0 0 353 | 354 | # 35 KEV 355 | .n 35 1 9 356 | 1 1 357 | 0 0 358 | 359 | # 36 ADPRc 360 | .n 36 1 18 361 | 1 1 362 | 0 0 363 | 364 | # 37 Ca2_ATPase 365 | .n 37 1 9 366 | 1 1 367 | 0 0 368 | 369 | # 38 NIA12 370 | .n 38 1 19 371 | 1 1 372 | 0 0 373 | 374 | # 39 Closure 375 | .n 39 5 4 7 25 27 31 376 | 11111 0 377 | 11110 0 378 | 11101 1 379 | 11100 1 380 | 11011 0 381 | 11010 0 382 | 11001 0 383 | 11000 0 384 | 10111 0 385 | 10110 0 386 | 10101 0 387 | 10100 0 388 | 10011 0 389 | 10010 0 390 | 10001 0 391 | 10000 0 392 | 01111 0 393 | 01110 0 394 | 01101 1 395 | 01100 0 396 | 01011 0 397 | 01010 0 398 | 01001 0 399 | 01000 0 400 | 00111 0 401 | 00110 0 402 | 00101 0 403 | 00100 0 404 | 00011 0 405 | 00010 0 406 | 00001 0 407 | 00000 0 408 | 409 | # 40 PLD 410 | .n 40 1 6 411 | 1 1 412 | 0 0 413 | 414 | # 41 ERA1 415 | .n 41 0 416 | 417 | # 42 ABA 418 | .n 42 0 419 | 420 | # 43 GCR1 421 | .n 43 0 422 | 423 | # 44 ABH1 424 | .n 44 0 425 | 426 | .e End of file 427 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/HCC1954 Breast Cell Line Short-term ErbB Network.txt: -------------------------------------------------------------------------------- 1 | .v 16 2 | 3 | .l 1 PLCg 4 | .l 2 ERBB2 5 | .l 3 PDK1 6 | .l 4 ERBB3 7 | .l 5 ERBB1 8 | .l 6 PKCa 9 | .l 7 mTOR 10 | .l 8 AKT 11 | .l 9 p70S6K 12 | .l 10 ERK1_2 13 | .l 11 MEK1_2 14 | .l 12 HRG 15 | .l 13 pertuzumab 16 | .l 14 EGF 17 | .l 15 erlotinib 18 | .l 16 trastuzumab 19 | 20 | # 1 PLCg 21 | .n 1 4 1 2 4 5 22 | 1111 1 23 | 1110 1 24 | 1101 1 25 | 1100 1 26 | 1011 1 27 | 1010 1 28 | 1001 1 29 | 1000 1 30 | 0111 1 31 | 0110 1 32 | 0101 1 33 | 0100 1 34 | 0011 1 35 | 0010 1 36 | 0001 1 37 | 0000 0 38 | 39 | # 2 ERBB2 40 | .n 2 6 2 3 5 13 15 16 41 | 111111 0 42 | 111110 0 43 | 111101 0 44 | 111100 0 45 | 111011 0 46 | 111010 0 47 | 111001 0 48 | 111000 1 49 | 110111 0 50 | 110110 0 51 | 110101 0 52 | 110100 0 53 | 110011 0 54 | 110010 0 55 | 110001 0 56 | 110000 1 57 | 101111 0 58 | 101110 0 59 | 101101 0 60 | 101100 0 61 | 101011 0 62 | 101010 0 63 | 101001 0 64 | 101000 1 65 | 100111 0 66 | 100110 0 67 | 100101 0 68 | 100100 0 69 | 100011 0 70 | 100010 0 71 | 100001 0 72 | 100000 1 73 | 011111 0 74 | 011110 0 75 | 011101 0 76 | 011100 0 77 | 011011 0 78 | 011010 0 79 | 011001 0 80 | 011000 1 81 | 010111 0 82 | 010110 0 83 | 010101 0 84 | 010100 0 85 | 010011 0 86 | 010010 0 87 | 010001 0 88 | 010000 1 89 | 001111 0 90 | 001110 0 91 | 001101 0 92 | 001100 0 93 | 001011 0 94 | 001010 0 95 | 001001 0 96 | 001000 1 97 | 000111 0 98 | 000110 0 99 | 000101 0 100 | 000100 0 101 | 000011 0 102 | 000010 0 103 | 000001 0 104 | 000000 0 105 | 106 | # 3 PDK1 107 | .n 3 4 2 3 4 5 108 | 1111 1 109 | 1110 1 110 | 1101 1 111 | 1100 1 112 | 1011 1 113 | 1010 1 114 | 1001 1 115 | 1000 1 116 | 0111 1 117 | 0110 1 118 | 0101 1 119 | 0100 1 120 | 0011 1 121 | 0010 1 122 | 0001 1 123 | 0000 0 124 | 125 | # 4 ERBB3 126 | .n 4 5 4 10 12 13 15 127 | 11111 0 128 | 11110 0 129 | 11101 0 130 | 11100 1 131 | 11011 0 132 | 11010 0 133 | 11001 0 134 | 11000 1 135 | 10111 0 136 | 10110 0 137 | 10101 0 138 | 10100 1 139 | 10011 0 140 | 10010 0 141 | 10001 0 142 | 10000 1 143 | 01111 0 144 | 01110 0 145 | 01101 0 146 | 01100 1 147 | 01011 0 148 | 01010 0 149 | 01001 0 150 | 01000 1 151 | 00111 0 152 | 00110 0 153 | 00101 0 154 | 00100 1 155 | 00011 0 156 | 00010 0 157 | 00001 0 158 | 00000 0 159 | 160 | # 5 ERBB1 161 | .n 5 5 1 5 13 14 15 162 | 11111 0 163 | 11110 0 164 | 11101 0 165 | 11100 0 166 | 11011 0 167 | 11010 1 168 | 11001 0 169 | 11000 1 170 | 10111 0 171 | 10110 0 172 | 10101 0 173 | 10100 0 174 | 10011 0 175 | 10010 1 176 | 10001 0 177 | 10000 1 178 | 01111 0 179 | 01110 0 180 | 01101 0 181 | 01100 0 182 | 01011 0 183 | 01010 1 184 | 01001 0 185 | 01000 1 186 | 00111 0 187 | 00110 0 188 | 00101 0 189 | 00100 0 190 | 00011 0 191 | 00010 1 192 | 00001 0 193 | 00000 0 194 | 195 | # 6 PKCa 196 | .n 6 3 1 6 16 197 | 111 1 198 | 110 1 199 | 101 1 200 | 100 1 201 | 011 1 202 | 010 1 203 | 001 1 204 | 000 0 205 | 206 | # 7 mTOR 207 | .n 7 2 7 8 208 | 11 1 209 | 10 1 210 | 01 1 211 | 00 0 212 | 213 | # 8 AKT 214 | .n 8 5 3 4 7 8 9 215 | 11111 1 216 | 11110 1 217 | 11101 1 218 | 11100 1 219 | 11011 1 220 | 11010 1 221 | 11001 1 222 | 11000 1 223 | 10111 1 224 | 10110 1 225 | 10101 1 226 | 10100 1 227 | 10011 1 228 | 10010 1 229 | 10001 1 230 | 10000 1 231 | 01111 1 232 | 01110 1 233 | 01101 1 234 | 01100 1 235 | 01011 1 236 | 01010 1 237 | 01001 1 238 | 01000 1 239 | 00111 1 240 | 00110 1 241 | 00101 1 242 | 00100 1 243 | 00011 1 244 | 00010 1 245 | 00001 1 246 | 00000 0 247 | 248 | # 9 p70S6K 249 | .n 9 5 7 8 9 10 15 250 | 11111 1 251 | 11110 1 252 | 11101 1 253 | 11100 1 254 | 11011 1 255 | 11010 1 256 | 11001 1 257 | 11000 1 258 | 10111 1 259 | 10110 1 260 | 10101 1 261 | 10100 1 262 | 10011 1 263 | 10010 1 264 | 10001 1 265 | 10000 1 266 | 01111 1 267 | 01110 1 268 | 01101 1 269 | 01100 1 270 | 01011 1 271 | 01010 1 272 | 01001 1 273 | 01000 1 274 | 00111 1 275 | 00110 1 276 | 00101 1 277 | 00100 1 278 | 00011 1 279 | 00010 1 280 | 00001 1 281 | 00000 0 282 | 283 | # 10 ERK1_2 284 | .n 10 2 10 11 285 | 11 1 286 | 10 1 287 | 01 1 288 | 00 0 289 | 290 | # 11 MEK1_2 291 | .n 11 5 2 3 4 5 11 292 | 11111 1 293 | 11110 1 294 | 11101 1 295 | 11100 1 296 | 11011 1 297 | 11010 1 298 | 11001 1 299 | 11000 1 300 | 10111 1 301 | 10110 1 302 | 10101 1 303 | 10100 1 304 | 10011 1 305 | 10010 1 306 | 10001 1 307 | 10000 1 308 | 01111 1 309 | 01110 1 310 | 01101 1 311 | 01100 1 312 | 01011 1 313 | 01010 1 314 | 01001 1 315 | 01000 1 316 | 00111 1 317 | 00110 1 318 | 00101 1 319 | 00100 1 320 | 00011 1 321 | 00010 1 322 | 00001 1 323 | 00000 0 324 | 325 | # 12 HRG 326 | .n 12 0 327 | 328 | # 13 pertuzumab 329 | .n 13 0 330 | 331 | # 14 EGF 332 | .n 14 0 333 | 334 | # 15 erlotinib 335 | .n 15 0 336 | 337 | # 16 trastuzumab 338 | .n 16 0 339 | 340 | .e End of file 341 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Iron acquisition and oxidative stress response in aspergillus fumigatus.txt: -------------------------------------------------------------------------------- 1 | .v 22 2 | 3 | .l 1 ROS 4 | .l 2 ThP 5 | .l 3 Yap1 6 | .l 4 Cat1/2 7 | .l 5 hapX 8 | .l 6 SidA 9 | .l 7 SreA 10 | .l 8 ICP 11 | .l 9 VAC 12 | .l 10 SOD2/3 13 | .l 11 HapX 14 | .l 12 MirB 15 | .l 13 sreA 16 | .l 14 EstB 17 | .l 15 FCplusFe 18 | .l 16 CccA 19 | .l 17 FCminusFe 20 | .l 18 TAFC 21 | .l 19 LIP 22 | .l 20 RIA 23 | .l 21 Superoxide 24 | .l 22 Iron 25 | 26 | # 1 ROS 27 | .n 1 6 1 2 4 10 19 21 28 | 111111 1 29 | 111110 1 30 | 111101 0 31 | 111100 0 32 | 111011 1 33 | 111010 1 34 | 111001 1 35 | 111000 1 36 | 110111 1 37 | 110110 1 38 | 110101 1 39 | 110100 0 40 | 110011 1 41 | 110010 1 42 | 110001 1 43 | 110000 1 44 | 101111 1 45 | 101110 1 46 | 101101 1 47 | 101100 0 48 | 101011 1 49 | 101010 1 50 | 101001 1 51 | 101000 1 52 | 100111 1 53 | 100110 1 54 | 100101 1 55 | 100100 1 56 | 100011 1 57 | 100010 1 58 | 100001 1 59 | 100000 1 60 | 011111 1 61 | 011110 1 62 | 011101 0 63 | 011100 0 64 | 011011 1 65 | 011010 1 66 | 011001 1 67 | 011000 0 68 | 010111 1 69 | 010110 1 70 | 010101 1 71 | 010100 0 72 | 010011 1 73 | 010010 1 74 | 010001 1 75 | 010000 0 76 | 001111 1 77 | 001110 1 78 | 001101 1 79 | 001100 0 80 | 001011 1 81 | 001010 1 82 | 001001 1 83 | 001000 0 84 | 000111 1 85 | 000110 1 86 | 000101 1 87 | 000100 0 88 | 000011 1 89 | 000010 1 90 | 000001 1 91 | 000000 0 92 | 93 | # 2 ThP 94 | .n 2 1 3 95 | 1 1 96 | 0 0 97 | 98 | # 3 Yap1 99 | .n 3 1 1 100 | 1 1 101 | 0 0 102 | 103 | # 4 Cat1/2 104 | .n 4 2 3 11 105 | 11 0 106 | 10 1 107 | 01 0 108 | 00 0 109 | 110 | # 5 hapX 111 | .n 5 1 7 112 | 1 0 113 | 0 1 114 | 115 | # 6 SidA 116 | .n 6 2 7 11 117 | 11 0 118 | 10 0 119 | 01 1 120 | 00 0 121 | 122 | # 7 SreA 123 | .n 7 2 13 19 124 | 11 1 125 | 10 0 126 | 01 0 127 | 00 0 128 | 129 | # 8 ICP 130 | .n 8 3 9 11 15 131 | 111 0 132 | 110 0 133 | 101 1 134 | 100 1 135 | 011 0 136 | 010 0 137 | 001 1 138 | 000 0 139 | 140 | # 9 VAC 141 | .n 9 2 16 19 142 | 11 1 143 | 10 0 144 | 01 0 145 | 00 0 146 | 147 | # 10 SOD2/3 148 | .n 10 1 3 149 | 1 1 150 | 0 0 151 | 152 | # 11 HapX 153 | .n 11 2 5 19 154 | 11 0 155 | 10 1 156 | 01 0 157 | 00 0 158 | 159 | # 12 MirB 160 | .n 12 2 7 11 161 | 11 0 162 | 10 0 163 | 01 1 164 | 00 0 165 | 166 | # 13 sreA 167 | .n 13 1 11 168 | 1 0 169 | 0 1 170 | 171 | # 14 EstB 172 | .n 14 1 7 173 | 1 0 174 | 0 1 175 | 176 | # 15 FCplusFe 177 | .n 15 2 17 19 178 | 11 1 179 | 10 0 180 | 01 0 181 | 00 0 182 | 183 | # 16 CccA 184 | .n 16 1 11 185 | 1 0 186 | 0 1 187 | 188 | # 17 FCminusFe 189 | .n 17 1 6 190 | 1 1 191 | 0 0 192 | 193 | # 18 TAFC 194 | .n 18 1 6 195 | 1 1 196 | 0 0 197 | 198 | # 19 LIP 199 | .n 19 5 12 14 18 20 22 200 | 11111 1 201 | 11110 1 202 | 11101 1 203 | 11100 1 204 | 11011 1 205 | 11010 0 206 | 11001 0 207 | 11000 0 208 | 10111 1 209 | 10110 0 210 | 10101 0 211 | 10100 0 212 | 10011 1 213 | 10010 0 214 | 10001 0 215 | 10000 0 216 | 01111 1 217 | 01110 0 218 | 01101 0 219 | 01100 0 220 | 01011 1 221 | 01010 0 222 | 01001 0 223 | 01000 0 224 | 00111 1 225 | 00110 0 226 | 00101 0 227 | 00100 0 228 | 00011 1 229 | 00010 0 230 | 00001 0 231 | 00000 0 232 | 233 | # 20 RIA 234 | .n 20 1 7 235 | 1 0 236 | 0 1 237 | 238 | # 21 Superoxide 239 | .n 21 0 240 | 241 | # 22 Iron 242 | .n 22 0 243 | 244 | .e End of file 245 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Lac Operon.txt: -------------------------------------------------------------------------------- 1 | .v 13 2 | 3 | .l 1 L 4 | .l 2 P 5 | .l 3 B 6 | .l 4 Rm 7 | .l 5 M 8 | .l 6 Am 9 | .l 7 A 10 | .l 8 C 11 | .l 9 Lm 12 | .l 10 R 13 | .l 11 Ge 14 | .l 12 Le 15 | .l 13 Lem 16 | 17 | # 1 L 18 | .n 1 3 11 12 2 19 | 111 0 20 | 110 0 21 | 101 0 22 | 100 0 23 | 011 1 24 | 010 0 25 | 001 0 26 | 000 0 27 | 28 | # 2 P 29 | .n 2 1 5 30 | 1 1 31 | 0 0 32 | 33 | # 3 B 34 | .n 3 1 5 35 | 1 1 36 | 0 0 37 | 38 | # 4 Rm 39 | .n 4 3 10 7 6 40 | 111 1 41 | 110 1 42 | 101 1 43 | 100 1 44 | 011 0 45 | 010 0 46 | 001 0 47 | 000 1 48 | 49 | # 5 M 50 | .n 5 3 10 4 8 51 | 111 0 52 | 110 0 53 | 101 0 54 | 100 0 55 | 011 0 56 | 010 0 57 | 001 1 58 | 000 0 59 | 60 | # 6 Am 61 | .n 6 2 9 1 62 | 11 1 63 | 10 1 64 | 01 1 65 | 00 0 66 | 67 | # 7 A 68 | .n 7 2 3 1 69 | 11 1 70 | 10 0 71 | 01 0 72 | 00 0 73 | 74 | # 8 C 75 | .n 8 1 11 76 | 1 0 77 | 0 1 78 | 79 | # 9 Lm 80 | .n 9 4 11 12 2 13 81 | 1111 0 82 | 1110 0 83 | 1101 0 84 | 1100 0 85 | 1011 0 86 | 1010 0 87 | 1001 0 88 | 1000 0 89 | 0111 1 90 | 0110 1 91 | 0101 1 92 | 0100 1 93 | 0011 1 94 | 0010 0 95 | 0001 0 96 | 0000 0 97 | 98 | # 10 R 99 | .n 10 2 6 7 100 | 11 0 101 | 10 0 102 | 01 0 103 | 00 1 104 | 105 | # 11 Ge 106 | .n 11 0 107 | 108 | # 12 Le 109 | .n 12 0 110 | 111 | # 13 Lem 112 | .n 13 0 113 | 114 | .e End of file 115 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Mammalian Cell Cycle 2006.txt: -------------------------------------------------------------------------------- 1 | .v 10 2 | 3 | .l 1 Rb 4 | .l 2 Cdc20 5 | .l 3 CycA 6 | .l 4 UbcH10 7 | .l 5 p27 8 | .l 6 CycD 9 | .l 7 CycE 10 | .l 8 Cdh1 11 | .l 9 CycB 12 | .l 10 E2F 13 | 14 | # 1 Rb 15 | .n 1 5 3 5 6 7 9 16 | 11111 0 17 | 11110 0 18 | 11101 0 19 | 11100 0 20 | 11011 0 21 | 11010 1 22 | 11001 0 23 | 11000 1 24 | 10111 0 25 | 10110 0 26 | 10101 0 27 | 10100 0 28 | 10011 0 29 | 10010 0 30 | 10001 0 31 | 10000 0 32 | 01111 0 33 | 01110 0 34 | 01101 0 35 | 01100 0 36 | 01011 0 37 | 01010 1 38 | 01001 0 39 | 01000 1 40 | 00111 0 41 | 00110 0 42 | 00101 0 43 | 00100 0 44 | 00011 0 45 | 00010 0 46 | 00001 0 47 | 00000 1 48 | 49 | # 2 Cdc20 50 | .n 2 1 9 51 | 1 1 52 | 0 0 53 | 54 | # 3 CycA 55 | .n 3 6 1 2 3 4 8 10 56 | 111111 0 57 | 111110 0 58 | 111101 0 59 | 111100 0 60 | 111011 0 61 | 111010 0 62 | 111001 0 63 | 111000 0 64 | 110111 0 65 | 110110 0 66 | 110101 0 67 | 110100 0 68 | 110011 0 69 | 110010 0 70 | 110001 0 71 | 110000 0 72 | 101111 0 73 | 101110 0 74 | 101101 0 75 | 101100 0 76 | 101011 0 77 | 101010 0 78 | 101001 0 79 | 101000 0 80 | 100111 0 81 | 100110 0 82 | 100101 0 83 | 100100 0 84 | 100011 0 85 | 100010 0 86 | 100001 0 87 | 100000 0 88 | 011111 0 89 | 011110 0 90 | 011101 0 91 | 011100 0 92 | 011011 0 93 | 011010 0 94 | 011001 0 95 | 011000 0 96 | 010111 0 97 | 010110 0 98 | 010101 0 99 | 010100 0 100 | 010011 0 101 | 010010 0 102 | 010001 0 103 | 010000 0 104 | 001111 0 105 | 001110 0 106 | 001101 1 107 | 001100 1 108 | 001011 1 109 | 001010 1 110 | 001001 1 111 | 001000 1 112 | 000111 0 113 | 000110 0 114 | 000101 1 115 | 000100 0 116 | 000011 1 117 | 000010 0 118 | 000001 1 119 | 000000 0 120 | 121 | # 4 UbcH10 122 | .n 4 5 2 3 4 8 9 123 | 11111 1 124 | 11110 1 125 | 11101 1 126 | 11100 1 127 | 11011 0 128 | 11010 0 129 | 11001 1 130 | 11000 1 131 | 10111 1 132 | 10110 1 133 | 10101 1 134 | 10100 1 135 | 10011 0 136 | 10010 0 137 | 10001 1 138 | 10000 1 139 | 01111 1 140 | 01110 1 141 | 01101 1 142 | 01100 1 143 | 01011 0 144 | 01010 0 145 | 01001 1 146 | 01000 1 147 | 00111 1 148 | 00110 0 149 | 00101 1 150 | 00100 1 151 | 00011 0 152 | 00010 0 153 | 00001 1 154 | 00000 1 155 | 156 | # 5 p27 157 | .n 5 5 3 5 6 7 9 158 | 11111 0 159 | 11110 0 160 | 11101 0 161 | 11100 0 162 | 11011 0 163 | 11010 0 164 | 11001 0 165 | 11000 1 166 | 10111 0 167 | 10110 0 168 | 10101 0 169 | 10100 0 170 | 10011 0 171 | 10010 0 172 | 10001 0 173 | 10000 0 174 | 01111 0 175 | 01110 0 176 | 01101 0 177 | 01100 0 178 | 01011 0 179 | 01010 1 180 | 01001 0 181 | 01000 1 182 | 00111 0 183 | 00110 0 184 | 00101 0 185 | 00100 0 186 | 00011 0 187 | 00010 0 188 | 00001 0 189 | 00000 1 190 | 191 | # 6 CycD 192 | .n 6 1 6 193 | 1 1 194 | 0 0 195 | 196 | # 7 CycE 197 | .n 7 2 1 10 198 | 11 0 199 | 10 0 200 | 01 1 201 | 00 0 202 | 203 | # 8 Cdh1 204 | .n 8 4 2 3 5 9 205 | 1111 1 206 | 1110 1 207 | 1101 1 208 | 1100 1 209 | 1011 1 210 | 1010 1 211 | 1001 1 212 | 1000 1 213 | 0111 0 214 | 0110 1 215 | 0101 0 216 | 0100 0 217 | 0011 0 218 | 0010 1 219 | 0001 0 220 | 0000 1 221 | 222 | # 9 CycB 223 | .n 9 2 2 8 224 | 11 0 225 | 10 0 226 | 01 0 227 | 00 1 228 | 229 | # 10 E2F 230 | .n 10 4 1 3 5 9 231 | 1111 0 232 | 1110 0 233 | 1101 0 234 | 1100 0 235 | 1011 0 236 | 1010 0 237 | 1001 0 238 | 1000 0 239 | 0111 0 240 | 0110 1 241 | 0101 0 242 | 0100 0 243 | 0011 0 244 | 0010 1 245 | 0001 0 246 | 0000 1 247 | 248 | .e End of file 249 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Mammalian Cell Cycle.txt: -------------------------------------------------------------------------------- 1 | .v 20 2 | 3 | .l 1 Akt1 4 | .l 2 ErbB1_3 5 | .l 3 pRB 6 | .l 4 IGF1R 7 | .l 5 CycD1 8 | .l 6 MEK1 9 | .l 7 CDK4 10 | .l 8 CDK6 11 | .l 9 ErbB1 12 | .l 10 ErbB2 13 | .l 11 p27 14 | .l 12 CycE1 15 | .l 13 ErbB1_2 16 | .l 14 CDK2 17 | .l 15 p21 18 | .l 16 ErbB2_3 19 | .l 17 cMYC 20 | .l 18 ErbB3 21 | .l 19 ERa 22 | .l 20 EGF 23 | 24 | # 1 Akt1 25 | .n 1 5 2 4 9 13 16 26 | 11111 1 27 | 11110 1 28 | 11101 1 29 | 11100 1 30 | 11011 1 31 | 11010 1 32 | 11001 1 33 | 11000 1 34 | 10111 1 35 | 10110 1 36 | 10101 1 37 | 10100 1 38 | 10011 1 39 | 10010 1 40 | 10001 1 41 | 10000 1 42 | 01111 1 43 | 01110 1 44 | 01101 1 45 | 01100 1 46 | 01011 1 47 | 01010 1 48 | 01001 1 49 | 01000 1 50 | 00111 1 51 | 00110 1 52 | 00101 1 53 | 00100 1 54 | 00011 1 55 | 00010 1 56 | 00001 1 57 | 00000 0 58 | 59 | # 2 ErbB1_3 60 | .n 2 2 9 18 61 | 11 1 62 | 10 0 63 | 01 0 64 | 00 0 65 | 66 | # 3 pRB 67 | .n 3 3 7 8 14 68 | 111 1 69 | 110 1 70 | 101 0 71 | 100 0 72 | 011 0 73 | 010 0 74 | 001 0 75 | 000 0 76 | 77 | # 4 IGF1R 78 | .n 4 3 1 16 19 79 | 111 0 80 | 110 0 81 | 101 1 82 | 100 1 83 | 011 0 84 | 010 0 85 | 001 1 86 | 000 0 87 | 88 | # 5 CycD1 89 | .n 5 4 1 6 17 19 90 | 1111 1 91 | 1110 0 92 | 1101 0 93 | 1100 0 94 | 1011 1 95 | 1010 0 96 | 1001 0 97 | 1000 0 98 | 0111 1 99 | 0110 0 100 | 0101 0 101 | 0100 0 102 | 0011 0 103 | 0010 0 104 | 0001 0 105 | 0000 0 106 | 107 | # 6 MEK1 108 | .n 6 5 2 4 9 13 16 109 | 11111 1 110 | 11110 1 111 | 11101 1 112 | 11100 1 113 | 11011 1 114 | 11010 1 115 | 11001 1 116 | 11000 1 117 | 10111 1 118 | 10110 1 119 | 10101 1 120 | 10100 1 121 | 10011 1 122 | 10010 1 123 | 10001 1 124 | 10000 1 125 | 01111 1 126 | 01110 1 127 | 01101 1 128 | 01100 1 129 | 01011 1 130 | 01010 1 131 | 01001 1 132 | 01000 1 133 | 00111 1 134 | 00110 1 135 | 00101 1 136 | 00100 1 137 | 00011 1 138 | 00010 1 139 | 00001 1 140 | 00000 0 141 | 142 | # 7 CDK4 143 | .n 7 3 5 11 15 144 | 111 0 145 | 110 0 146 | 101 0 147 | 100 1 148 | 011 0 149 | 010 0 150 | 001 0 151 | 000 0 152 | 153 | # 8 CDK6 154 | .n 8 1 5 155 | 1 1 156 | 0 0 157 | 158 | # 9 ErbB1 159 | .n 9 1 20 160 | 1 1 161 | 0 0 162 | 163 | # 10 ErbB2 164 | .n 10 1 20 165 | 1 1 166 | 0 0 167 | 168 | # 11 p27 169 | .n 11 5 1 7 14 17 19 170 | 11111 0 171 | 11110 0 172 | 11101 0 173 | 11100 0 174 | 11011 0 175 | 11010 0 176 | 11001 0 177 | 11000 0 178 | 10111 0 179 | 10110 0 180 | 10101 0 181 | 10100 0 182 | 10011 0 183 | 10010 0 184 | 10001 0 185 | 10000 0 186 | 01111 0 187 | 01110 0 188 | 01101 0 189 | 01100 0 190 | 01011 0 191 | 01010 0 192 | 01001 0 193 | 01000 0 194 | 00111 0 195 | 00110 0 196 | 00101 0 197 | 00100 0 198 | 00011 0 199 | 00010 0 200 | 00001 1 201 | 00000 0 202 | 203 | # 12 CycE1 204 | .n 12 1 17 205 | 1 1 206 | 0 0 207 | 208 | # 13 ErbB1_2 209 | .n 13 2 9 10 210 | 11 1 211 | 10 0 212 | 01 0 213 | 00 0 214 | 215 | # 14 CDK2 216 | .n 14 3 11 12 15 217 | 111 0 218 | 110 0 219 | 101 0 220 | 100 0 221 | 011 0 222 | 010 1 223 | 001 0 224 | 000 0 225 | 226 | # 15 p21 227 | .n 15 4 1 7 17 19 228 | 1111 0 229 | 1110 0 230 | 1101 0 231 | 1100 0 232 | 1011 0 233 | 1010 0 234 | 1001 0 235 | 1000 0 236 | 0111 0 237 | 0110 0 238 | 0101 0 239 | 0100 0 240 | 0011 0 241 | 0010 0 242 | 0001 1 243 | 0000 0 244 | 245 | # 16 ErbB2_3 246 | .n 16 2 10 18 247 | 11 1 248 | 10 0 249 | 01 0 250 | 00 0 251 | 252 | # 17 cMYC 253 | .n 17 3 1 6 19 254 | 111 1 255 | 110 1 256 | 101 1 257 | 100 1 258 | 011 1 259 | 010 1 260 | 001 1 261 | 000 0 262 | 263 | # 18 ErbB3 264 | .n 18 1 20 265 | 1 1 266 | 0 0 267 | 268 | # 19 ERa 269 | .n 19 2 1 6 270 | 11 1 271 | 10 1 272 | 01 1 273 | 00 0 274 | 275 | # 20 EGF 276 | .n 20 0 277 | 278 | .e End of file 279 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Metabolic Interactions in the Gut Microbiome.txt: -------------------------------------------------------------------------------- 1 | .v 12 2 | 3 | .l 1 Mollicutes 4 | .l 2 Akkermansia 5 | .l 3 Blautia 6 | .l 4 Clostridium_difficile 7 | .l 5 Lachnospiraceae_other 8 | .l 6 Lachnospiraceae 9 | .l 7 Other 10 | .l 8 Enterobacteriaceae 11 | .l 9 Clindamycin 12 | .l 10 Enterococcus 13 | .l 11 Barnesiella 14 | .l 12 Coprobacillus 15 | 16 | # 1 Mollicutes 17 | .n 1 1 1 18 | 1 1 19 | 0 0 20 | 21 | # 2 Akkermansia 22 | .n 2 1 12 23 | 1 1 24 | 0 0 25 | 26 | # 3 Blautia 27 | .n 3 3 3 10 12 28 | 111 1 29 | 110 1 30 | 101 1 31 | 100 1 32 | 011 1 33 | 010 1 34 | 001 1 35 | 000 0 36 | 37 | # 4 Clostridium_difficile 38 | .n 4 2 4 11 39 | 11 0 40 | 10 1 41 | 01 0 42 | 00 0 43 | 44 | # 5 Lachnospiraceae_other 45 | .n 5 4 5 6 7 9 46 | 1111 0 47 | 1110 1 48 | 1101 0 49 | 1100 1 50 | 1011 0 51 | 1010 1 52 | 1001 0 53 | 1000 1 54 | 0111 0 55 | 0110 1 56 | 0101 0 57 | 0100 1 58 | 0011 0 59 | 0010 1 60 | 0001 0 61 | 0000 0 62 | 63 | # 6 Lachnospiraceae 64 | .n 6 4 5 6 7 9 65 | 1111 0 66 | 1110 1 67 | 1101 0 68 | 1100 1 69 | 1011 0 70 | 1010 1 71 | 1001 0 72 | 1000 1 73 | 0111 0 74 | 0110 1 75 | 0101 0 76 | 0100 1 77 | 0011 0 78 | 0010 1 79 | 0001 0 80 | 0000 0 81 | 82 | # 7 Other 83 | .n 7 4 5 6 7 9 84 | 1111 0 85 | 1110 1 86 | 1101 0 87 | 1100 1 88 | 1011 0 89 | 1010 1 90 | 1001 0 91 | 1000 1 92 | 0111 0 93 | 0110 1 94 | 0101 0 95 | 0100 1 96 | 0011 0 97 | 0010 1 98 | 0001 0 99 | 0000 0 100 | 101 | # 8 Enterobacteriaceae 102 | .n 8 1 8 103 | 1 1 104 | 0 0 105 | 106 | # 9 Clindamycin 107 | .n 9 1 9 108 | 1 1 109 | 0 0 110 | 111 | # 10 Enterococcus 112 | .n 10 5 1 3 4 8 12 113 | 11111 1 114 | 11110 1 115 | 11101 1 116 | 11100 1 117 | 11011 1 118 | 11010 1 119 | 11001 1 120 | 11000 1 121 | 10111 1 122 | 10110 1 123 | 10101 1 124 | 10100 1 125 | 10011 1 126 | 10010 1 127 | 10001 1 128 | 10000 1 129 | 01111 1 130 | 01110 1 131 | 01101 1 132 | 01100 1 133 | 01011 1 134 | 01010 1 135 | 01001 1 136 | 01000 1 137 | 00111 1 138 | 00110 1 139 | 00101 1 140 | 00100 1 141 | 00011 1 142 | 00010 1 143 | 00001 0 144 | 00000 1 145 | 146 | # 11 Barnesiella 147 | .n 11 4 5 6 7 9 148 | 1111 0 149 | 1110 1 150 | 1101 0 151 | 1100 1 152 | 1011 0 153 | 1010 1 154 | 1001 0 155 | 1000 1 156 | 0111 0 157 | 0110 1 158 | 0101 0 159 | 0100 1 160 | 0011 0 161 | 0010 1 162 | 0001 0 163 | 0000 0 164 | 165 | # 12 Coprobacillus 166 | .n 12 0 167 | 168 | .e End of file 169 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Neurotransmitter Signaling Pathway.txt: -------------------------------------------------------------------------------- 1 | .v 16 2 | 3 | .l 1 Calcium 4 | .l 2 Packaging_Proteins 5 | .l 3 Calcineurin 6 | .l 4 COMT 7 | .l 5 Exocytosis 8 | .l 6 Protein_Phosphatase_1 9 | .l 7 Tryosine_hydroxylase 10 | .l 8 Protein_Kinase_A 11 | .l 9 Phospholipase_C 12 | .l 10 Glutamate_Receptor 13 | .l 11 DARPP32 14 | .l 12 Dopamine_Receptor_2 15 | .l 13 Adenylate_cyclase 16 | .l 14 Dopamine 17 | .l 15 Dopamine_Receptor_1 18 | .l 16 Glutamate 19 | 20 | # 1 Calcium 21 | .n 1 2 9 10 22 | 11 1 23 | 10 1 24 | 01 1 25 | 00 0 26 | 27 | # 2 Packaging_Proteins 28 | .n 2 1 10 29 | 1 1 30 | 0 0 31 | 32 | # 3 Calcineurin 33 | .n 3 1 1 34 | 1 1 35 | 0 0 36 | 37 | # 4 COMT 38 | .n 4 1 14 39 | 1 1 40 | 0 0 41 | 42 | # 5 Exocytosis 43 | .n 5 1 2 44 | 1 1 45 | 0 0 46 | 47 | # 6 Protein_Phosphatase_1 48 | .n 6 1 11 49 | 1 0 50 | 0 1 51 | 52 | # 7 Tryosine_hydroxylase 53 | .n 7 1 7 54 | 1 1 55 | 0 0 56 | 57 | # 8 Protein_Kinase_A 58 | .n 8 1 13 59 | 1 1 60 | 0 0 61 | 62 | # 9 Phospholipase_C 63 | .n 9 1 12 64 | 1 1 65 | 0 0 66 | 67 | # 10 Glutamate_Receptor 68 | .n 10 3 6 8 16 69 | 111 0 70 | 110 0 71 | 101 0 72 | 100 0 73 | 011 1 74 | 010 0 75 | 001 0 76 | 000 0 77 | 78 | # 11 DARPP32 79 | .n 11 2 3 8 80 | 11 0 81 | 10 0 82 | 01 1 83 | 00 0 84 | 85 | # 12 Dopamine_Receptor_2 86 | .n 12 1 14 87 | 1 1 88 | 0 0 89 | 90 | # 13 Adenylate_cyclase 91 | .n 13 2 12 15 92 | 11 0 93 | 10 0 94 | 01 1 95 | 00 0 96 | 97 | # 14 Dopamine 98 | .n 14 2 4 7 99 | 11 0 100 | 10 0 101 | 01 1 102 | 00 0 103 | 104 | # 15 Dopamine_Receptor_1 105 | .n 15 1 14 106 | 1 1 107 | 0 0 108 | 109 | # 16 Glutamate 110 | .n 16 1 16 111 | 1 1 112 | 0 0 113 | 114 | .e End of file 115 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Oxidative Stress Pathway.txt: -------------------------------------------------------------------------------- 1 | .v 19 2 | 3 | .l 1 PKC 4 | .l 2 Mdm2 5 | .l 3 PIP3 6 | .l 4 Bach1 7 | .l 5 p53 8 | .l 6 Ras 9 | .l 7 ROS 10 | .l 8 ARE 11 | .l 9 ATM 12 | .l 10 Bad 13 | .l 11 GSK3b 14 | .l 12 PTEN 15 | .l 13 Nrf2 16 | .l 14 PIP2 17 | .l 15 PI3K 18 | .l 16 Keap1 19 | .l 17 Bcl2 20 | .l 18 Akt 21 | .l 19 Stress 22 | 23 | # 1 PKC 24 | .n 1 2 7 8 25 | 11 0 26 | 10 1 27 | 01 0 28 | 00 0 29 | 30 | # 2 Mdm2 31 | .n 2 3 5 9 18 32 | 111 0 33 | 110 0 34 | 101 1 35 | 100 1 36 | 011 0 37 | 010 0 38 | 001 1 39 | 000 0 40 | 41 | # 3 PIP3 42 | .n 3 2 12 14 43 | 11 0 44 | 10 0 45 | 01 1 46 | 00 0 47 | 48 | # 4 Bach1 49 | .n 4 1 7 50 | 1 0 51 | 0 1 52 | 53 | # 5 p53 54 | .n 5 2 2 9 55 | 11 0 56 | 10 0 57 | 01 1 58 | 00 0 59 | 60 | # 6 Ras 61 | .n 6 1 7 62 | 1 1 63 | 0 0 64 | 65 | # 7 ROS 66 | .n 7 2 8 19 67 | 11 0 68 | 10 0 69 | 01 1 70 | 00 0 71 | 72 | # 8 ARE 73 | .n 8 4 4 8 11 13 74 | 1111 0 75 | 1110 0 76 | 1101 0 77 | 1100 0 78 | 1011 0 79 | 1010 0 80 | 1001 0 81 | 1000 0 82 | 0111 0 83 | 0110 0 84 | 0101 0 85 | 0100 0 86 | 0011 0 87 | 0010 0 88 | 0001 1 89 | 0000 0 90 | 91 | # 9 ATM 92 | .n 9 1 7 93 | 1 1 94 | 0 0 95 | 96 | # 10 Bad 97 | .n 10 1 18 98 | 1 0 99 | 0 1 100 | 101 | # 11 GSK3b 102 | .n 11 1 18 103 | 1 0 104 | 0 1 105 | 106 | # 12 PTEN 107 | .n 12 1 7 108 | 1 0 109 | 0 1 110 | 111 | # 13 Nrf2 112 | .n 13 3 1 16 18 113 | 111 1 114 | 110 1 115 | 101 1 116 | 100 1 117 | 011 1 118 | 010 0 119 | 001 1 120 | 000 1 121 | 122 | # 14 PIP2 123 | .n 14 1 15 124 | 1 1 125 | 0 0 126 | 127 | # 15 PI3K 128 | .n 15 1 6 129 | 1 1 130 | 0 0 131 | 132 | # 16 Keap1 133 | .n 16 3 4 13 16 134 | 111 0 135 | 110 0 136 | 101 0 137 | 100 0 138 | 011 1 139 | 010 1 140 | 001 1 141 | 000 0 142 | 143 | # 17 Bcl2 144 | .n 17 2 5 10 145 | 11 0 146 | 10 0 147 | 01 0 148 | 00 1 149 | 150 | # 18 Akt 151 | .n 18 1 3 152 | 1 1 153 | 0 0 154 | 155 | # 19 Stress 156 | .n 19 0 157 | 158 | .e End of file 159 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/PC12 Cell Differentiation.txt: -------------------------------------------------------------------------------- 1 | .v 62 2 | 3 | .l 1 Plasmin 4 | .l 2 FAK 5 | .l 3 uPA/PLAT 6 | .l 4 TrkA 7 | .l 5 Fosl1 8 | .l 6 RAS 9 | .l 7 MSK1/2 10 | .l 8 Maff 11 | .l 9 KLF2 12 | .l 10 KLF5 13 | .l 11 RSK 14 | .l 12 Stat3 15 | .l 13 DAG 16 | .l 14 FRS2 17 | .l 15 MKK6 18 | .l 16 G(i/o) 19 | .l 17 KLF6 20 | .l 18 P38 21 | .l 19 Dusp6 22 | .l 20 Mmp3/10 23 | .l 21 ATF2 24 | .l 22 P53 25 | .l 23 SRF 26 | .l 24 RAP1 27 | .l 25 AKT 28 | .l 26 Npy 29 | .l 27 ETS1 30 | .l 28 Ca2+ 31 | .l 29 Egr1 32 | .l 30 ECM 33 | .l 31 Itga1 34 | .l 32 MKK7 35 | .l 33 MEKK4 36 | .l 34 GRB2 37 | .l 35 MEK 38 | .l 36 JUND 39 | .l 37 JNK 40 | .l 38 MYC 41 | .l 39 PI3K 42 | .l 40 ZFP36 43 | .l 41 NPYY1 44 | .l 42 PKC 45 | .l 43 KLF10 46 | .l 44 JUNB 47 | .l 45 AP1 48 | .l 46 CREB 49 | .l 47 FOS 50 | .l 48 PLC 51 | .l 49 RAF 52 | .l 50 Mapk3k 53 | .l 51 BTG2 54 | .l 52 CITED2 55 | .l 53 MEKK1 56 | .l 54 uPAR 57 | .l 55 KLF4 58 | .l 56 RAC1 59 | .l 57 SOS 60 | .l 58 ARC 61 | .l 59 SHC 62 | .l 60 ERK 63 | .l 61 C3G 64 | .l 62 NGF 65 | 66 | # 1 Plasmin 67 | .n 1 1 3 68 | 1 1 69 | 0 0 70 | 71 | # 2 FAK 72 | .n 2 2 24 31 73 | 11 1 74 | 10 1 75 | 01 1 76 | 00 0 77 | 78 | # 3 uPA/PLAT 79 | .n 3 1 54 80 | 1 1 81 | 0 0 82 | 83 | # 4 TrkA 84 | .n 4 1 62 85 | 1 1 86 | 0 0 87 | 88 | # 5 Fosl1 89 | .n 5 3 25 37 60 90 | 111 1 91 | 110 1 92 | 101 1 93 | 100 1 94 | 011 1 95 | 010 1 96 | 001 1 97 | 000 0 98 | 99 | # 6 RAS 100 | .n 6 1 57 101 | 1 1 102 | 0 0 103 | 104 | # 7 MSK1/2 105 | .n 7 2 18 60 106 | 11 1 107 | 10 1 108 | 01 1 109 | 00 0 110 | 111 | # 8 Maff 112 | .n 8 3 21 37 60 113 | 111 1 114 | 110 1 115 | 101 1 116 | 100 1 117 | 011 1 118 | 010 1 119 | 001 1 120 | 000 0 121 | 122 | # 9 KLF2 123 | .n 9 3 25 37 60 124 | 111 1 125 | 110 1 126 | 101 1 127 | 100 1 128 | 011 1 129 | 010 1 130 | 001 1 131 | 000 0 132 | 133 | # 10 KLF5 134 | .n 10 3 22 25 60 135 | 111 1 136 | 110 1 137 | 101 1 138 | 100 1 139 | 011 1 140 | 010 1 141 | 001 1 142 | 000 0 143 | 144 | # 11 RSK 145 | .n 11 1 60 146 | 1 1 147 | 0 0 148 | 149 | # 12 Stat3 150 | .n 12 2 37 60 151 | 11 1 152 | 10 1 153 | 01 1 154 | 00 0 155 | 156 | # 13 DAG 157 | .n 13 1 48 158 | 1 1 159 | 0 0 160 | 161 | # 14 FRS2 162 | .n 14 1 4 163 | 1 1 164 | 0 0 165 | 166 | # 15 MKK6 167 | .n 15 1 33 168 | 1 1 169 | 0 0 170 | 171 | # 16 G(i/o) 172 | .n 16 1 41 173 | 1 1 174 | 0 0 175 | 176 | # 17 KLF6 177 | .n 17 2 22 37 178 | 11 1 179 | 10 1 180 | 01 1 181 | 00 0 182 | 183 | # 18 P38 184 | .n 18 2 15 50 185 | 11 1 186 | 10 1 187 | 01 1 188 | 00 0 189 | 190 | # 19 Dusp6 191 | .n 19 1 27 192 | 1 1 193 | 0 0 194 | 195 | # 20 Mmp3/10 196 | .n 20 1 1 197 | 1 1 198 | 0 0 199 | 200 | # 21 ATF2 201 | .n 21 3 18 37 60 202 | 111 1 203 | 110 1 204 | 101 1 205 | 100 1 206 | 011 1 207 | 010 1 208 | 001 1 209 | 000 0 210 | 211 | # 22 P53 212 | .n 22 3 25 37 60 213 | 111 1 214 | 110 1 215 | 101 1 216 | 100 1 217 | 011 1 218 | 010 1 219 | 001 1 220 | 000 0 221 | 222 | # 23 SRF 223 | .n 23 1 11 224 | 1 1 225 | 0 0 226 | 227 | # 24 RAP1 228 | .n 24 1 61 229 | 1 1 230 | 0 0 231 | 232 | # 25 AKT 233 | .n 25 1 39 234 | 1 1 235 | 0 0 236 | 237 | # 26 Npy 238 | .n 26 1 45 239 | 1 1 240 | 0 0 241 | 242 | # 27 ETS1 243 | .n 27 2 37 60 244 | 11 1 245 | 10 1 246 | 01 1 247 | 00 0 248 | 249 | # 28 Ca2+ 250 | .n 28 1 48 251 | 1 1 252 | 0 0 253 | 254 | # 29 Egr1 255 | .n 29 3 25 37 60 256 | 111 1 257 | 110 1 258 | 101 1 259 | 100 1 260 | 011 1 261 | 010 1 262 | 001 1 263 | 000 0 264 | 265 | # 30 ECM 266 | .n 30 1 20 267 | 1 1 268 | 0 0 269 | 270 | # 31 Itga1 271 | .n 31 1 30 272 | 1 1 273 | 0 0 274 | 275 | # 32 MKK7 276 | .n 32 1 53 277 | 1 1 278 | 0 0 279 | 280 | # 33 MEKK4 281 | .n 33 1 56 282 | 1 1 283 | 0 0 284 | 285 | # 34 GRB2 286 | .n 34 1 59 287 | 1 1 288 | 0 0 289 | 290 | # 35 MEK 291 | .n 35 2 49 53 292 | 11 1 293 | 10 1 294 | 01 1 295 | 00 0 296 | 297 | # 36 JUND 298 | .n 36 2 37 60 299 | 11 1 300 | 10 1 301 | 01 1 302 | 00 0 303 | 304 | # 37 JNK 305 | .n 37 2 32 33 306 | 11 1 307 | 10 1 308 | 01 1 309 | 00 0 310 | 311 | # 38 MYC 312 | .n 38 3 25 37 60 313 | 111 1 314 | 110 1 315 | 101 1 316 | 100 1 317 | 011 1 318 | 010 1 319 | 001 1 320 | 000 0 321 | 322 | # 39 PI3K 323 | .n 39 1 4 324 | 1 1 325 | 0 0 326 | 327 | # 40 ZFP36 328 | .n 40 2 37 60 329 | 11 1 330 | 10 1 331 | 01 1 332 | 00 0 333 | 334 | # 41 NPYY1 335 | .n 41 1 26 336 | 1 1 337 | 0 0 338 | 339 | # 42 PKC 340 | .n 42 2 13 28 341 | 11 1 342 | 10 1 343 | 01 1 344 | 00 0 345 | 346 | # 43 KLF10 347 | .n 43 3 25 37 60 348 | 111 1 349 | 110 1 350 | 101 1 351 | 100 1 352 | 011 1 353 | 010 1 354 | 001 1 355 | 000 0 356 | 357 | # 44 JUNB 358 | .n 44 3 25 37 60 359 | 111 1 360 | 110 1 361 | 101 1 362 | 100 1 363 | 011 1 364 | 010 1 365 | 001 1 366 | 000 0 367 | 368 | # 45 AP1 369 | .n 45 4 5 36 44 47 370 | 1111 1 371 | 1110 1 372 | 1101 1 373 | 1100 1 374 | 1011 1 375 | 1010 1 376 | 1001 1 377 | 1000 1 378 | 0111 1 379 | 0110 1 380 | 0101 1 381 | 0100 1 382 | 0011 1 383 | 0010 1 384 | 0001 1 385 | 0000 0 386 | 387 | # 46 CREB 388 | .n 46 3 7 11 25 389 | 111 1 390 | 110 1 391 | 101 1 392 | 100 1 393 | 011 1 394 | 010 1 395 | 001 1 396 | 000 0 397 | 398 | # 47 FOS 399 | .n 47 3 25 37 60 400 | 111 1 401 | 110 1 402 | 101 1 403 | 100 1 404 | 011 1 405 | 010 1 406 | 001 1 407 | 000 0 408 | 409 | # 48 PLC 410 | .n 48 2 4 16 411 | 11 1 412 | 10 1 413 | 01 1 414 | 00 0 415 | 416 | # 49 RAF 417 | .n 49 2 6 42 418 | 11 1 419 | 10 1 420 | 01 1 421 | 00 0 422 | 423 | # 50 Mapk3k 424 | .n 50 1 33 425 | 1 1 426 | 0 0 427 | 428 | # 51 BTG2 429 | .n 51 2 25 37 430 | 11 1 431 | 10 1 432 | 01 1 433 | 00 0 434 | 435 | # 52 CITED2 436 | .n 52 3 22 46 60 437 | 111 1 438 | 110 1 439 | 101 1 440 | 100 1 441 | 011 1 442 | 010 1 443 | 001 1 444 | 000 0 445 | 446 | # 53 MEKK1 447 | .n 53 1 56 448 | 1 1 449 | 0 0 450 | 451 | # 54 uPAR 452 | .n 54 1 45 453 | 1 1 454 | 0 0 455 | 456 | # 55 KLF4 457 | .n 55 3 25 37 60 458 | 111 1 459 | 110 1 460 | 101 1 461 | 100 1 462 | 011 1 463 | 010 1 464 | 001 1 465 | 000 0 466 | 467 | # 56 RAC1 468 | .n 56 1 6 469 | 1 1 470 | 0 0 471 | 472 | # 57 SOS 473 | .n 57 1 34 474 | 1 1 475 | 0 0 476 | 477 | # 58 ARC 478 | .n 58 2 29 46 479 | 11 1 480 | 10 1 481 | 01 1 482 | 00 0 483 | 484 | # 59 SHC 485 | .n 59 2 2 4 486 | 11 1 487 | 10 1 488 | 01 1 489 | 00 0 490 | 491 | # 60 ERK 492 | .n 60 1 35 493 | 1 1 494 | 0 0 495 | 496 | # 61 C3G 497 | .n 61 1 14 498 | 1 1 499 | 0 0 500 | 501 | # 62 NGF 502 | .n 62 0 503 | 504 | .e End of file 505 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Predicting Variabilities in Cardiac Gene.txt: -------------------------------------------------------------------------------- 1 | .v 15 2 | 3 | .l 1 Nkx2.5 4 | .l 2 GATAs 5 | .l 3 Mesp1 6 | .l 4 Bmp2 7 | .l 5 Tbx5 8 | .l 6 exogen_CanWnt_I 9 | .l 7 Isl1 10 | .l 8 exogen_CanWnt_II 11 | .l 9 Dkk1 12 | .l 10 Tbx1 13 | .l 11 Foxc1.2 14 | .l 12 exogen_BMP2_II 15 | .l 13 canWnt 16 | .l 14 Fgf8 17 | .l 15 exogen_BMP2_I 18 | 19 | # 1 Nkx2.5 20 | .n 1 7 2 3 4 5 7 9 10 21 | 1111111 1 22 | 1111110 1 23 | 1111101 1 24 | 1111100 1 25 | 1111011 1 26 | 1111010 1 27 | 1111001 1 28 | 1111000 1 29 | 1110111 1 30 | 1110110 1 31 | 1110101 1 32 | 1110100 1 33 | 1110011 1 34 | 1110010 1 35 | 1110001 1 36 | 1110000 1 37 | 1101111 1 38 | 1101110 1 39 | 1101101 1 40 | 1101100 1 41 | 1101011 1 42 | 1101010 1 43 | 1101001 1 44 | 1101000 1 45 | 1100111 1 46 | 1100110 1 47 | 1100101 1 48 | 1100100 1 49 | 1100011 1 50 | 1100010 1 51 | 1100001 1 52 | 1100000 0 53 | 1011111 1 54 | 1011110 1 55 | 1011101 1 56 | 1011100 1 57 | 1011011 1 58 | 1011010 1 59 | 1011001 1 60 | 1011000 1 61 | 1010111 1 62 | 1010110 1 63 | 1010101 1 64 | 1010100 1 65 | 1010011 1 66 | 1010010 1 67 | 1010001 1 68 | 1010000 1 69 | 1001111 1 70 | 1001110 1 71 | 1001101 1 72 | 1001100 1 73 | 1001011 1 74 | 1001010 1 75 | 1001001 1 76 | 1001000 1 77 | 1000111 1 78 | 1000110 1 79 | 1000101 1 80 | 1000100 1 81 | 1000011 1 82 | 1000010 0 83 | 1000001 1 84 | 1000000 0 85 | 0111111 1 86 | 0111110 1 87 | 0111101 1 88 | 0111100 1 89 | 0111011 1 90 | 0111010 1 91 | 0111001 1 92 | 0111000 1 93 | 0110111 1 94 | 0110110 1 95 | 0110101 1 96 | 0110100 0 97 | 0110011 1 98 | 0110010 1 99 | 0110001 1 100 | 0110000 0 101 | 0101111 1 102 | 0101110 1 103 | 0101101 1 104 | 0101100 1 105 | 0101011 1 106 | 0101010 1 107 | 0101001 1 108 | 0101000 1 109 | 0100111 1 110 | 0100110 1 111 | 0100101 1 112 | 0100100 0 113 | 0100011 1 114 | 0100010 1 115 | 0100001 1 116 | 0100000 0 117 | 0011111 1 118 | 0011110 1 119 | 0011101 1 120 | 0011100 1 121 | 0011011 1 122 | 0011010 1 123 | 0011001 1 124 | 0011000 1 125 | 0010111 1 126 | 0010110 0 127 | 0010101 1 128 | 0010100 0 129 | 0010011 1 130 | 0010010 0 131 | 0010001 1 132 | 0010000 0 133 | 0001111 1 134 | 0001110 1 135 | 0001101 1 136 | 0001100 1 137 | 0001011 1 138 | 0001010 1 139 | 0001001 1 140 | 0001000 1 141 | 0000111 1 142 | 0000110 0 143 | 0000101 1 144 | 0000100 0 145 | 0000011 1 146 | 0000010 0 147 | 0000001 1 148 | 0000000 0 149 | 150 | # 2 GATAs 151 | .n 2 3 1 3 5 152 | 111 1 153 | 110 1 154 | 101 1 155 | 100 1 156 | 011 1 157 | 010 1 158 | 001 1 159 | 000 0 160 | 161 | # 3 Mesp1 162 | .n 3 2 12 13 163 | 11 0 164 | 10 0 165 | 01 1 166 | 00 0 167 | 168 | # 4 Bmp2 169 | .n 4 2 12 13 170 | 11 0 171 | 10 1 172 | 01 0 173 | 00 0 174 | 175 | # 5 Tbx5 176 | .n 5 6 1 3 5 9 10 13 177 | 111111 0 178 | 111110 0 179 | 111101 0 180 | 111100 1 181 | 111011 0 182 | 111010 0 183 | 111001 0 184 | 111000 1 185 | 110111 0 186 | 110110 0 187 | 110101 0 188 | 110100 1 189 | 110011 0 190 | 110010 0 191 | 110001 0 192 | 110000 1 193 | 101111 0 194 | 101110 0 195 | 101101 0 196 | 101100 1 197 | 101011 0 198 | 101010 0 199 | 101001 0 200 | 101000 1 201 | 100111 0 202 | 100110 0 203 | 100101 0 204 | 100100 0 205 | 100011 0 206 | 100010 0 207 | 100001 0 208 | 100000 1 209 | 011111 0 210 | 011110 0 211 | 011101 0 212 | 011100 1 213 | 011011 0 214 | 011010 0 215 | 011001 0 216 | 011000 1 217 | 010111 0 218 | 010110 0 219 | 010101 0 220 | 010100 1 221 | 010011 0 222 | 010010 0 223 | 010001 0 224 | 010000 1 225 | 001111 0 226 | 001110 0 227 | 001101 0 228 | 001100 1 229 | 001011 0 230 | 001010 0 231 | 001001 0 232 | 001000 1 233 | 000111 0 234 | 000110 0 235 | 000101 0 236 | 000100 0 237 | 000011 0 238 | 000010 0 239 | 000001 0 240 | 000000 0 241 | 242 | # 6 exogen_CanWnt_I 243 | .n 6 1 6 244 | 1 1 245 | 0 0 246 | 247 | # 7 Isl1 248 | .n 7 5 3 8 10 13 14 249 | 11111 1 250 | 11110 1 251 | 11101 1 252 | 11100 1 253 | 11011 1 254 | 11010 1 255 | 11001 1 256 | 11000 1 257 | 10111 1 258 | 10110 1 259 | 10101 1 260 | 10100 1 261 | 10011 1 262 | 10010 1 263 | 10001 1 264 | 10000 1 265 | 01111 1 266 | 01110 1 267 | 01101 1 268 | 01100 1 269 | 01011 1 270 | 01010 1 271 | 01001 1 272 | 01000 0 273 | 00111 1 274 | 00110 1 275 | 00101 1 276 | 00100 1 277 | 00011 1 278 | 00010 0 279 | 00001 1 280 | 00000 0 281 | 282 | # 8 exogen_CanWnt_II 283 | .n 8 1 6 284 | 1 1 285 | 0 0 286 | 287 | # 9 Dkk1 288 | .n 9 3 3 12 13 289 | 111 1 290 | 110 1 291 | 101 1 292 | 100 1 293 | 011 0 294 | 010 0 295 | 001 1 296 | 000 0 297 | 298 | # 10 Tbx1 299 | .n 10 1 11 300 | 1 1 301 | 0 0 302 | 303 | # 11 Foxc1.2 304 | .n 11 2 8 13 305 | 11 1 306 | 10 0 307 | 01 0 308 | 00 0 309 | 310 | # 12 exogen_BMP2_II 311 | .n 12 1 15 312 | 1 1 313 | 0 0 314 | 315 | # 13 canWnt 316 | .n 13 1 8 317 | 1 1 318 | 0 0 319 | 320 | # 14 Fgf8 321 | .n 14 3 3 10 11 322 | 111 0 323 | 110 0 324 | 101 0 325 | 100 0 326 | 011 1 327 | 010 1 328 | 001 1 329 | 000 0 330 | 331 | # 15 exogen_BMP2_I 332 | .n 15 0 333 | 334 | .e End of file 335 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Processing of Spz Network from the Drosophila Signaling Pathway.txt: -------------------------------------------------------------------------------- 1 | .v 24 2 | 3 | .l 1 ModSP 4 | .l 2 Spirit 5 | .l 3 PGRP_SD 6 | .l 4 Viru_Fact 7 | .l 5 DAP 8 | .l 6 SPE 9 | .l 7 GNBP3 10 | .l 8 Spd 11 | .l 9 GNBP1 12 | .l 10 Spz 13 | .l 11 Gd 14 | .l 12 Sphinx 15 | .l 13 Snk 16 | .l 14 Psh 17 | .l 15 Ndl 18 | .l 16 Easter 19 | .l 17 Grass 20 | .l 18 PGRP_SA 21 | .l 19 GramP_Bact 22 | .l 20 DV_patterning 23 | .l 21 Pipe 24 | .l 22 Nec 25 | .l 23 Fungi 26 | .l 24 GramN_Bact 27 | 28 | # 1 ModSP 29 | .n 1 4 3 7 9 18 30 | 1111 1 31 | 1110 1 32 | 1101 1 33 | 1100 1 34 | 1011 1 35 | 1010 1 36 | 1001 1 37 | 1000 1 38 | 0111 1 39 | 0110 1 40 | 0101 1 41 | 0100 1 42 | 0011 1 43 | 0010 1 44 | 0001 1 45 | 0000 0 46 | 47 | # 2 Spirit 48 | .n 2 1 17 49 | 1 1 50 | 0 0 51 | 52 | # 3 PGRP_SD 53 | .n 3 1 5 54 | 1 1 55 | 0 0 56 | 57 | # 4 Viru_Fact 58 | .n 4 2 19 23 59 | 11 1 60 | 10 1 61 | 01 1 62 | 00 0 63 | 64 | # 5 DAP 65 | .n 5 1 24 66 | 1 1 67 | 0 0 68 | 69 | # 6 SPE 70 | .n 6 5 2 8 12 14 16 71 | 11111 1 72 | 11110 1 73 | 11101 1 74 | 11100 1 75 | 11011 1 76 | 11010 1 77 | 11001 1 78 | 11000 1 79 | 10111 1 80 | 10110 1 81 | 10101 1 82 | 10100 1 83 | 10011 1 84 | 10010 1 85 | 10001 1 86 | 10000 1 87 | 01111 1 88 | 01110 1 89 | 01101 1 90 | 01100 1 91 | 01011 1 92 | 01010 1 93 | 01001 1 94 | 01000 1 95 | 00111 1 96 | 00110 1 97 | 00101 1 98 | 00100 1 99 | 00011 1 100 | 00010 1 101 | 00001 1 102 | 00000 0 103 | 104 | # 7 GNBP3 105 | .n 7 1 23 106 | 1 1 107 | 0 0 108 | 109 | # 8 Spd 110 | .n 8 1 17 111 | 1 1 112 | 0 0 113 | 114 | # 9 GNBP1 115 | .n 9 1 19 116 | 1 1 117 | 0 0 118 | 119 | # 10 Spz 120 | .n 10 1 6 121 | 1 1 122 | 0 0 123 | 124 | # 11 Gd 125 | .n 11 1 15 126 | 1 1 127 | 0 0 128 | 129 | # 12 Sphinx 130 | .n 12 1 17 131 | 1 1 132 | 0 0 133 | 134 | # 13 Snk 135 | .n 13 1 11 136 | 1 1 137 | 0 0 138 | 139 | # 14 Psh 140 | .n 14 2 4 22 141 | 11 0 142 | 10 1 143 | 01 0 144 | 00 0 145 | 146 | # 15 Ndl 147 | .n 15 1 20 148 | 1 1 149 | 0 0 150 | 151 | # 16 Easter 152 | .n 16 2 13 21 153 | 11 1 154 | 10 0 155 | 01 0 156 | 00 0 157 | 158 | # 17 Grass 159 | .n 17 1 1 160 | 1 1 161 | 0 0 162 | 163 | # 18 PGRP_SA 164 | .n 18 1 19 165 | 1 1 166 | 0 0 167 | 168 | # 19 GramP_Bact 169 | .n 19 0 170 | 171 | # 20 DV_patterning 172 | .n 20 0 173 | 174 | # 21 Pipe 175 | .n 21 0 176 | 177 | # 22 Nec 178 | .n 22 0 179 | 180 | # 23 Fungi 181 | .n 23 0 182 | 183 | # 24 GramN_Bact 184 | .n 24 0 185 | 186 | .e End of file 187 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Regulation of the L-arabinose operon of Escherichia coli.txt: -------------------------------------------------------------------------------- 1 | .v 13 2 | 3 | .l 1 L 4 | .l 2 C 5 | .l 3 MT 6 | .l 4 Am 7 | .l 5 T 8 | .l 6 Ara+ 9 | .l 7 E 10 | .l 8 MS 11 | .l 9 A 12 | .l 10 Ge 13 | .l 11 Ae 14 | .l 12 Ara- 15 | .l 13 Aem 16 | 17 | # 1 L 18 | .n 1 2 6 12 19 | 11 0 20 | 10 0 21 | 01 1 22 | 00 0 23 | 24 | # 2 C 25 | .n 2 1 10 26 | 1 0 27 | 0 1 28 | 29 | # 3 MT 30 | .n 3 2 2 6 31 | 11 1 32 | 10 0 33 | 01 0 34 | 00 0 35 | 36 | # 4 Am 37 | .n 4 3 5 11 13 38 | 111 1 39 | 110 1 40 | 101 1 41 | 100 0 42 | 011 1 43 | 010 1 44 | 001 0 45 | 000 0 46 | 47 | # 5 T 48 | .n 5 1 3 49 | 1 1 50 | 0 0 51 | 52 | # 6 Ara+ 53 | .n 6 3 4 9 12 54 | 111 1 55 | 110 0 56 | 101 1 57 | 100 0 58 | 011 1 59 | 010 0 60 | 001 0 61 | 000 0 62 | 63 | # 7 E 64 | .n 7 1 8 65 | 1 1 66 | 0 0 67 | 68 | # 8 MS 69 | .n 8 2 2 6 70 | 11 1 71 | 10 0 72 | 01 0 73 | 00 0 74 | 75 | # 9 A 76 | .n 9 2 5 11 77 | 11 1 78 | 10 0 79 | 01 0 80 | 00 0 81 | 82 | # 10 Ge 83 | .n 10 0 84 | 85 | # 11 Ae 86 | .n 11 0 87 | 88 | # 12 Ara- 89 | .n 12 0 90 | 91 | # 13 Aem 92 | .n 13 0 93 | 94 | .e End of file 95 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/SKBR3 Breast Cell Line Short-term ErbB Network.txt: -------------------------------------------------------------------------------- 1 | .v 16 2 | 3 | .l 1 ERBB3 4 | .l 2 ERK1_2 5 | .l 3 PDK1 6 | .l 4 PLCg 7 | .l 5 p70S6K 8 | .l 6 ERBB1 9 | .l 7 MEK1_2 10 | .l 8 PKCa 11 | .l 9 ERBB2 12 | .l 10 mTOR 13 | .l 11 AKT 14 | .l 12 HRG 15 | .l 13 trastuzumab 16 | .l 14 erlotinib 17 | .l 15 pertuzumab 18 | .l 16 EGF 19 | 20 | # 1 ERBB3 21 | .n 1 4 1 12 14 15 22 | 1111 0 23 | 1110 0 24 | 1101 0 25 | 1100 1 26 | 1011 0 27 | 1010 0 28 | 1001 0 29 | 1000 1 30 | 0111 0 31 | 0110 0 32 | 0101 0 33 | 0100 1 34 | 0011 0 35 | 0010 0 36 | 0001 0 37 | 0000 0 38 | 39 | # 2 ERK1_2 40 | .n 2 4 1 2 3 7 41 | 1111 1 42 | 1110 1 43 | 1101 1 44 | 1100 1 45 | 1011 1 46 | 1010 1 47 | 1001 1 48 | 1000 1 49 | 0111 1 50 | 0110 1 51 | 0101 1 52 | 0100 1 53 | 0011 1 54 | 0010 1 55 | 0001 1 56 | 0000 0 57 | 58 | # 3 PDK1 59 | .n 3 4 1 3 6 9 60 | 1111 1 61 | 1110 1 62 | 1101 1 63 | 1100 1 64 | 1011 1 65 | 1010 1 66 | 1001 1 67 | 1000 1 68 | 0111 1 69 | 0110 1 70 | 0101 1 71 | 0100 1 72 | 0011 1 73 | 0010 1 74 | 0001 1 75 | 0000 0 76 | 77 | # 4 PLCg 78 | .n 4 4 1 4 6 9 79 | 1111 1 80 | 1110 1 81 | 1101 1 82 | 1100 1 83 | 1011 1 84 | 1010 1 85 | 1001 1 86 | 1000 1 87 | 0111 1 88 | 0110 1 89 | 0101 1 90 | 0100 1 91 | 0011 1 92 | 0010 1 93 | 0001 1 94 | 0000 0 95 | 96 | # 5 p70S6K 97 | .n 5 4 2 5 10 11 98 | 1111 1 99 | 1110 1 100 | 1101 1 101 | 1100 1 102 | 1011 1 103 | 1010 1 104 | 1001 1 105 | 1000 1 106 | 0111 1 107 | 0110 1 108 | 0101 1 109 | 0100 1 110 | 0011 1 111 | 0010 1 112 | 0001 1 113 | 0000 0 114 | 115 | # 6 ERBB1 116 | .n 6 5 4 6 14 15 16 117 | 11111 0 118 | 11110 0 119 | 11101 0 120 | 11100 0 121 | 11011 0 122 | 11010 0 123 | 11001 1 124 | 11000 1 125 | 10111 0 126 | 10110 0 127 | 10101 0 128 | 10100 0 129 | 10011 0 130 | 10010 0 131 | 10001 1 132 | 10000 1 133 | 01111 0 134 | 01110 0 135 | 01101 0 136 | 01100 0 137 | 01011 0 138 | 01010 0 139 | 01001 1 140 | 01000 1 141 | 00111 0 142 | 00110 0 143 | 00101 0 144 | 00100 0 145 | 00011 0 146 | 00010 0 147 | 00001 1 148 | 00000 0 149 | 150 | # 7 MEK1_2 151 | .n 7 4 1 6 7 9 152 | 1111 1 153 | 1110 1 154 | 1101 1 155 | 1100 1 156 | 1011 1 157 | 1010 1 158 | 1001 1 159 | 1000 1 160 | 0111 1 161 | 0110 1 162 | 0101 1 163 | 0100 1 164 | 0011 1 165 | 0010 1 166 | 0001 1 167 | 0000 0 168 | 169 | # 8 PKCa 170 | .n 8 2 4 8 171 | 11 1 172 | 10 1 173 | 01 1 174 | 00 0 175 | 176 | # 9 ERBB2 177 | .n 9 4 9 13 14 15 178 | 1111 0 179 | 1110 0 180 | 1101 0 181 | 1100 0 182 | 1011 0 183 | 1010 0 184 | 1001 0 185 | 1000 1 186 | 0111 0 187 | 0110 0 188 | 0101 0 189 | 0100 0 190 | 0011 0 191 | 0010 0 192 | 0001 0 193 | 0000 0 194 | 195 | # 10 mTOR 196 | .n 10 2 10 11 197 | 11 1 198 | 10 1 199 | 01 1 200 | 00 0 201 | 202 | # 11 AKT 203 | .n 11 4 1 3 10 11 204 | 1111 1 205 | 1110 1 206 | 1101 1 207 | 1100 1 208 | 1011 1 209 | 1010 1 210 | 1001 1 211 | 1000 1 212 | 0111 1 213 | 0110 1 214 | 0101 1 215 | 0100 1 216 | 0011 1 217 | 0010 1 218 | 0001 1 219 | 0000 0 220 | 221 | # 12 HRG 222 | .n 12 0 223 | 224 | # 13 trastuzumab 225 | .n 13 0 226 | 227 | # 14 erlotinib 228 | .n 14 0 229 | 230 | # 15 pertuzumab 231 | .n 15 0 232 | 233 | # 16 EGF 234 | .n 16 0 235 | 236 | .e End of file 237 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Senescence Associated Secretory Phenotype.txt: -------------------------------------------------------------------------------- 1 | .v 51 2 | 3 | .l 1 JAK 4 | .l 2 cFos 5 | .l 3 TAK1 6 | .l 4 MKK 7 | .l 5 Oncogene 8 | .l 6 RB 9 | .l 7 CEBPbeta 10 | .l 8 NFkB 11 | .l 9 CDK4 12 | .l 10 ATR 13 | .l 11 CHK1 14 | .l 12 IRAK 15 | .l 13 ATM 16 | .l 14 IL1 17 | .l 15 MEKK 18 | .l 16 ERK1_2 19 | .l 17 MEK1_2 20 | .l 18 Elk1 21 | .l 19 p53 22 | .l 20 IkB 23 | .l 21 CHK2 24 | .l 22 TRAF6 25 | .l 23 SOCS3 26 | .l 24 TAB 27 | .l 25 CDK2 28 | .l 26 cJun 29 | .l 27 MDM2 30 | .l 28 p38 31 | .l 29 p16INK4 32 | .l 30 HIF1 33 | .l 31 IL6 34 | .l 32 JNK 35 | .l 33 NIK 36 | .l 34 GP130 37 | .l 35 IL6R 38 | .l 36 IKK 39 | .l 37 PI3K 40 | .l 38 AP1 41 | .l 39 Akt 42 | .l 40 mTOR 43 | .l 41 E2F 44 | .l 42 p21 45 | .l 43 IL8 46 | .l 44 pRB 47 | .l 45 IL1R 48 | .l 46 NEMO 49 | .l 47 MKP1 50 | .l 48 MyD88 51 | .l 49 STAT3 52 | .l 50 Hypoxia 53 | .l 51 DNAD 54 | 55 | # 1 JAK 56 | .n 1 2 23 35 57 | 11 0 58 | 10 0 59 | 01 1 60 | 00 0 61 | 62 | # 2 cFos 63 | .n 2 5 7 18 28 32 49 64 | 11111 1 65 | 11110 1 66 | 11101 1 67 | 11100 1 68 | 11011 1 69 | 11010 1 70 | 11001 1 71 | 11000 1 72 | 10111 1 73 | 10110 1 74 | 10101 1 75 | 10100 1 76 | 10011 1 77 | 10010 1 78 | 10001 1 79 | 10000 1 80 | 01111 1 81 | 01110 1 82 | 01101 1 83 | 01100 1 84 | 01011 1 85 | 01010 1 86 | 01001 1 87 | 01000 1 88 | 00111 1 89 | 00110 1 90 | 00101 1 91 | 00100 1 92 | 00011 1 93 | 00010 1 94 | 00001 1 95 | 00000 0 96 | 97 | # 3 TAK1 98 | .n 3 2 22 24 99 | 11 1 100 | 10 1 101 | 01 1 102 | 00 0 103 | 104 | # 4 MKK 105 | .n 4 2 3 15 106 | 11 1 107 | 10 1 108 | 01 1 109 | 00 0 110 | 111 | # 5 Oncogene 112 | .n 5 2 31 43 113 | 11 1 114 | 10 1 115 | 01 1 116 | 00 0 117 | 118 | # 6 RB 119 | .n 6 3 9 25 44 120 | 111 0 121 | 110 0 122 | 101 0 123 | 100 0 124 | 011 0 125 | 010 0 126 | 001 0 127 | 000 1 128 | 129 | # 7 CEBPbeta 130 | .n 7 1 18 131 | 1 1 132 | 0 0 133 | 134 | # 8 NFkB 135 | .n 8 2 20 36 136 | 11 0 137 | 10 0 138 | 01 1 139 | 00 0 140 | 141 | # 9 CDK4 142 | .n 9 2 29 42 143 | 11 0 144 | 10 0 145 | 01 0 146 | 00 1 147 | 148 | # 10 ATR 149 | .n 10 1 51 150 | 1 1 151 | 0 0 152 | 153 | # 11 CHK1 154 | .n 11 1 10 155 | 1 1 156 | 0 0 157 | 158 | # 12 IRAK 159 | .n 12 3 12 45 48 160 | 111 1 161 | 110 1 162 | 101 1 163 | 100 1 164 | 011 1 165 | 010 1 166 | 001 1 167 | 000 0 168 | 169 | # 13 ATM 170 | .n 13 1 51 171 | 1 1 172 | 0 0 173 | 174 | # 14 IL1 175 | .n 14 1 8 176 | 1 1 177 | 0 0 178 | 179 | # 15 MEKK 180 | .n 15 1 22 181 | 1 1 182 | 0 0 183 | 184 | # 16 ERK1_2 185 | .n 16 2 17 31 186 | 11 1 187 | 10 0 188 | 01 0 189 | 00 0 190 | 191 | # 17 MEK1_2 192 | .n 17 2 31 34 193 | 11 1 194 | 10 0 195 | 01 0 196 | 00 0 197 | 198 | # 18 Elk1 199 | .n 18 1 16 200 | 1 1 201 | 0 0 202 | 203 | # 19 p53 204 | .n 19 4 11 13 21 27 205 | 1111 0 206 | 1110 1 207 | 1101 0 208 | 1100 1 209 | 1011 0 210 | 1010 1 211 | 1001 0 212 | 1000 1 213 | 0111 0 214 | 0110 1 215 | 0101 0 216 | 0100 1 217 | 0011 0 218 | 0010 1 219 | 0001 0 220 | 0000 0 221 | 222 | # 20 IkB 223 | .n 20 4 8 20 36 46 224 | 1111 0 225 | 1110 1 226 | 1101 1 227 | 1100 1 228 | 1011 0 229 | 1010 1 230 | 1001 1 231 | 1000 1 232 | 0111 0 233 | 0110 1 234 | 0101 1 235 | 0100 1 236 | 0011 0 237 | 0010 0 238 | 0001 0 239 | 0000 0 240 | 241 | # 21 CHK2 242 | .n 21 1 13 243 | 1 1 244 | 0 0 245 | 246 | # 22 TRAF6 247 | .n 22 1 12 248 | 1 1 249 | 0 0 250 | 251 | # 23 SOCS3 252 | .n 23 1 49 253 | 1 1 254 | 0 0 255 | 256 | # 24 TAB 257 | .n 24 2 12 22 258 | 11 1 259 | 10 1 260 | 01 1 261 | 00 0 262 | 263 | # 25 CDK2 264 | .n 25 2 41 42 265 | 11 0 266 | 10 1 267 | 01 0 268 | 00 0 269 | 270 | # 26 cJun 271 | .n 26 5 2 7 16 28 32 272 | 11111 1 273 | 11110 1 274 | 11101 1 275 | 11100 1 276 | 11011 1 277 | 11010 1 278 | 11001 1 279 | 11000 1 280 | 10111 1 281 | 10110 1 282 | 10101 1 283 | 10100 1 284 | 10011 1 285 | 10010 1 286 | 10001 1 287 | 10000 0 288 | 01111 0 289 | 01110 0 290 | 01101 0 291 | 01100 0 292 | 01011 0 293 | 01010 0 294 | 01001 0 295 | 01000 0 296 | 00111 0 297 | 00110 0 298 | 00101 0 299 | 00100 0 300 | 00011 0 301 | 00010 0 302 | 00001 0 303 | 00000 0 304 | 305 | # 27 MDM2 306 | .n 27 2 13 19 307 | 11 0 308 | 10 0 309 | 01 1 310 | 00 0 311 | 312 | # 28 p38 313 | .n 28 2 4 47 314 | 11 0 315 | 10 1 316 | 01 0 317 | 00 0 318 | 319 | # 29 p16INK4 320 | .n 29 2 5 51 321 | 11 1 322 | 10 1 323 | 01 1 324 | 00 0 325 | 326 | # 30 HIF1 327 | .n 30 2 19 50 328 | 11 0 329 | 10 0 330 | 01 1 331 | 00 0 332 | 333 | # 31 IL6 334 | .n 31 3 7 8 16 335 | 111 1 336 | 110 1 337 | 101 1 338 | 100 1 339 | 011 1 340 | 010 1 341 | 001 1 342 | 000 0 343 | 344 | # 32 JNK 345 | .n 32 2 4 47 346 | 11 0 347 | 10 1 348 | 01 0 349 | 00 0 350 | 351 | # 33 NIK 352 | .n 33 1 3 353 | 1 1 354 | 0 0 355 | 356 | # 34 GP130 357 | .n 34 1 31 358 | 1 1 359 | 0 0 360 | 361 | # 35 IL6R 362 | .n 35 1 31 363 | 1 1 364 | 0 0 365 | 366 | # 36 IKK 367 | .n 36 3 33 39 46 368 | 111 1 369 | 110 1 370 | 101 1 371 | 100 1 372 | 011 1 373 | 010 1 374 | 001 1 375 | 000 0 376 | 377 | # 37 PI3K 378 | .n 37 1 1 379 | 1 1 380 | 0 0 381 | 382 | # 38 AP1 383 | .n 38 2 2 26 384 | 11 1 385 | 10 0 386 | 01 0 387 | 00 0 388 | 389 | # 39 Akt 390 | .n 39 1 37 391 | 1 1 392 | 0 0 393 | 394 | # 40 mTOR 395 | .n 40 1 39 396 | 1 1 397 | 0 0 398 | 399 | # 41 E2F 400 | .n 41 3 6 41 44 401 | 111 0 402 | 110 0 403 | 101 0 404 | 100 0 405 | 011 1 406 | 010 1 407 | 001 1 408 | 000 0 409 | 410 | # 42 p21 411 | .n 42 2 19 30 412 | 11 1 413 | 10 1 414 | 01 1 415 | 00 0 416 | 417 | # 43 IL8 418 | .n 43 3 7 8 38 419 | 111 1 420 | 110 1 421 | 101 1 422 | 100 1 423 | 011 1 424 | 010 1 425 | 001 1 426 | 000 0 427 | 428 | # 44 pRB 429 | .n 44 2 9 25 430 | 11 1 431 | 10 1 432 | 01 1 433 | 00 0 434 | 435 | # 45 IL1R 436 | .n 45 1 14 437 | 1 1 438 | 0 0 439 | 440 | # 46 NEMO 441 | .n 46 1 51 442 | 1 1 443 | 0 0 444 | 445 | # 47 MKP1 446 | .n 47 1 38 447 | 1 1 448 | 0 0 449 | 450 | # 48 MyD88 451 | .n 48 1 45 452 | 1 1 453 | 0 0 454 | 455 | # 49 STAT3 456 | .n 49 4 1 2 26 40 457 | 1111 1 458 | 1110 1 459 | 1101 1 460 | 1100 1 461 | 1011 1 462 | 1010 1 463 | 1001 1 464 | 1000 1 465 | 0111 1 466 | 0110 1 467 | 0101 1 468 | 0100 0 469 | 0011 1 470 | 0010 0 471 | 0001 1 472 | 0000 0 473 | 474 | # 50 Hypoxia 475 | .n 50 0 476 | 477 | # 51 DNAD 478 | .n 51 0 479 | 480 | .e End of file 481 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Septation Initiation Network.txt: -------------------------------------------------------------------------------- 1 | .v 31 2 | 3 | .l 1 dma1 4 | .l 2 pom1 5 | .l 3 flp1 6 | .l 4 spg1 7 | .l 5 cdc42 8 | .l 6 cdc16 9 | .l 7 sid2 10 | .l 8 orb6 11 | .l 9 cdc7 12 | .l 10 SIP 13 | .l 11 Rga4 14 | .l 12 cdc11 15 | .l 13 byr4 16 | .l 14 fin1 17 | .l 15 sid4 18 | .l 16 plo1 19 | .l 17 pmo25 20 | .l 18 byr4-cdc16 21 | .l 19 scd1 22 | .l 20 pak1 23 | .l 21 cdc14-sid1 24 | .l 22 nak1 25 | .l 23 gef1 26 | .l 24 cdk-0 27 | .l 25 CK1 28 | .l 26 cdk-L 29 | .l 27 sid2-mob1 30 | .l 28 etd1 31 | .l 29 ppc89 32 | .l 30 cdk-H 33 | .l 31 ras1 34 | 35 | # 1 dma1 36 | .n 1 2 15 25 37 | 11 1 38 | 10 0 39 | 01 0 40 | 00 0 41 | 42 | # 2 pom1 43 | .n 2 1 20 44 | 1 1 45 | 0 0 46 | 47 | # 3 flp1 48 | .n 3 3 24 27 30 49 | 111 0 50 | 110 1 51 | 101 0 52 | 100 1 53 | 011 0 54 | 010 1 55 | 001 0 56 | 000 0 57 | 58 | # 4 spg1 59 | .n 4 3 12 18 28 60 | 111 0 61 | 110 0 62 | 101 1 63 | 100 1 64 | 011 0 65 | 010 0 66 | 001 1 67 | 000 0 68 | 69 | # 5 cdc42 70 | .n 5 3 11 19 23 71 | 111 0 72 | 110 0 73 | 101 0 74 | 100 0 75 | 011 1 76 | 010 1 77 | 001 1 78 | 000 0 79 | 80 | # 6 cdc16 81 | .n 6 1 14 82 | 1 0 83 | 0 1 84 | 85 | # 7 sid2 86 | .n 7 3 9 10 12 87 | 111 1 88 | 110 1 89 | 101 1 90 | 100 1 91 | 011 0 92 | 010 0 93 | 001 0 94 | 000 0 95 | 96 | # 8 orb6 97 | .n 8 2 20 22 98 | 11 1 99 | 10 1 100 | 01 1 101 | 00 0 102 | 103 | # 9 cdc7 104 | .n 9 2 4 12 105 | 11 1 106 | 10 0 107 | 01 0 108 | 00 0 109 | 110 | # 10 SIP 111 | .n 10 3 24 29 30 112 | 111 0 113 | 110 0 114 | 101 1 115 | 100 0 116 | 011 1 117 | 010 0 118 | 001 1 119 | 000 0 120 | 121 | # 11 Rga4 122 | .n 11 1 2 123 | 1 0 124 | 0 1 125 | 126 | # 12 cdc11 127 | .n 12 4 3 6 9 15 128 | 1111 1 129 | 1110 1 130 | 1101 1 131 | 1100 1 132 | 1011 1 133 | 1010 1 134 | 1001 1 135 | 1000 0 136 | 0111 1 137 | 0110 1 138 | 0101 1 139 | 0100 1 140 | 0011 1 141 | 0010 1 142 | 0001 1 143 | 0000 0 144 | 145 | # 13 byr4 146 | .n 13 4 5 16 26 30 147 | 1111 0 148 | 1110 0 149 | 1101 0 150 | 1100 0 151 | 1011 0 152 | 1010 0 153 | 1001 0 154 | 1000 0 155 | 0111 0 156 | 0110 1 157 | 0101 0 158 | 0100 0 159 | 0011 1 160 | 0010 1 161 | 0001 0 162 | 0000 0 163 | 164 | # 14 fin1 165 | .n 14 1 30 166 | 1 1 167 | 0 0 168 | 169 | # 15 sid4 170 | .n 15 1 29 171 | 1 1 172 | 0 0 173 | 174 | # 16 plo1 175 | .n 16 4 1 15 26 30 176 | 1111 0 177 | 1110 0 178 | 1101 0 179 | 1100 0 180 | 1011 0 181 | 1010 0 182 | 1001 1 183 | 1000 0 184 | 0111 1 185 | 0110 1 186 | 0101 1 187 | 0100 1 188 | 0011 0 189 | 0010 0 190 | 0001 1 191 | 0000 0 192 | 193 | # 17 pmo25 194 | .n 17 2 9 21 195 | 11 1 196 | 10 1 197 | 01 1 198 | 00 0 199 | 200 | # 18 byr4-cdc16 201 | .n 18 2 6 13 202 | 11 1 203 | 10 0 204 | 01 0 205 | 00 0 206 | 207 | # 19 scd1 208 | .n 19 1 31 209 | 1 1 210 | 0 0 211 | 212 | # 20 pak1 213 | .n 20 1 5 214 | 1 1 215 | 0 0 216 | 217 | # 21 cdc14-sid1 218 | .n 21 1 9 219 | 1 1 220 | 0 0 221 | 222 | # 22 nak1 223 | .n 22 3 17 27 30 224 | 111 1 225 | 110 1 226 | 101 1 227 | 100 1 228 | 011 1 229 | 010 0 230 | 001 0 231 | 000 0 232 | 233 | # 23 gef1 234 | .n 23 1 8 235 | 1 1 236 | 0 0 237 | 238 | # 24 cdk-0 239 | .n 24 0 240 | 241 | # 25 CK1 242 | .n 25 0 243 | 244 | # 26 cdk-L 245 | .n 26 0 246 | 247 | # 27 sid2-mob1 248 | .n 27 0 249 | 250 | # 28 etd1 251 | .n 28 0 252 | 253 | # 29 ppc89 254 | .n 29 0 255 | 256 | # 30 cdk-H 257 | .n 30 0 258 | 259 | # 31 ras1 260 | .n 31 0 261 | 262 | .e End of file 263 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/T cell differentiation.txt: -------------------------------------------------------------------------------- 1 | .v 23 2 | 3 | .l 1 NFAT 4 | .l 2 IRAK 5 | .l 3 STAT1 6 | .l 4 IL10R 7 | .l 5 IL12R 8 | .l 6 IL18R 9 | .l 7 IFNgR 10 | .l 8 IFNg 11 | .l 9 STAT4 12 | .l 10 IL10 13 | .l 11 STAT3 14 | .l 12 IFNbR 15 | .l 13 IL4 16 | .l 14 IL4R 17 | .l 15 GATA3 18 | .l 16 STAT6 19 | .l 17 SOCS1 20 | .l 18 JAK1 21 | .l 19 Tbet 22 | .l 20 IFNb 23 | .l 21 TCR 24 | .l 22 IL18 25 | .l 23 IL12 26 | 27 | # 1 NFAT 28 | .n 1 1 21 29 | 1 1 30 | 0 0 31 | 32 | # 2 IRAK 33 | .n 2 1 6 34 | 1 1 35 | 0 0 36 | 37 | # 3 STAT1 38 | .n 3 2 12 18 39 | 11 1 40 | 10 1 41 | 01 1 42 | 00 0 43 | 44 | # 4 IL10R 45 | .n 4 1 10 46 | 1 1 47 | 0 0 48 | 49 | # 5 IL12R 50 | .n 5 1 23 51 | 1 1 52 | 0 0 53 | 54 | # 6 IL18R 55 | .n 6 2 16 22 56 | 11 0 57 | 10 0 58 | 01 1 59 | 00 0 60 | 61 | # 7 IFNgR 62 | .n 7 1 8 63 | 1 1 64 | 0 0 65 | 66 | # 8 IFNg 67 | .n 8 5 1 2 9 11 19 68 | 11111 0 69 | 11110 0 70 | 11101 1 71 | 11100 1 72 | 11011 0 73 | 11010 0 74 | 11001 1 75 | 11000 1 76 | 10111 0 77 | 10110 0 78 | 10101 1 79 | 10100 1 80 | 10011 0 81 | 10010 0 82 | 10001 1 83 | 10000 1 84 | 01111 0 85 | 01110 0 86 | 01101 1 87 | 01100 1 88 | 01011 0 89 | 01010 0 90 | 01001 1 91 | 01000 1 92 | 00111 0 93 | 00110 0 94 | 00101 1 95 | 00100 1 96 | 00011 0 97 | 00010 0 98 | 00001 1 99 | 00000 0 100 | 101 | # 9 STAT4 102 | .n 9 2 5 15 103 | 11 0 104 | 10 1 105 | 01 0 106 | 00 0 107 | 108 | # 10 IL10 109 | .n 10 1 15 110 | 1 1 111 | 0 0 112 | 113 | # 11 STAT3 114 | .n 11 1 4 115 | 1 1 116 | 0 0 117 | 118 | # 12 IFNbR 119 | .n 12 1 20 120 | 1 1 121 | 0 0 122 | 123 | # 13 IL4 124 | .n 13 2 3 15 125 | 11 0 126 | 10 0 127 | 01 1 128 | 00 0 129 | 130 | # 14 IL4R 131 | .n 14 2 13 17 132 | 11 0 133 | 10 1 134 | 01 0 135 | 00 0 136 | 137 | # 15 GATA3 138 | .n 15 3 15 16 19 139 | 111 0 140 | 110 1 141 | 101 0 142 | 100 1 143 | 011 0 144 | 010 1 145 | 001 0 146 | 000 0 147 | 148 | # 16 STAT6 149 | .n 16 1 14 150 | 1 1 151 | 0 0 152 | 153 | # 17 SOCS1 154 | .n 17 2 3 19 155 | 11 1 156 | 10 1 157 | 01 1 158 | 00 0 159 | 160 | # 18 JAK1 161 | .n 18 2 7 17 162 | 11 0 163 | 10 1 164 | 01 0 165 | 00 0 166 | 167 | # 19 Tbet 168 | .n 19 3 3 15 19 169 | 111 0 170 | 110 0 171 | 101 1 172 | 100 1 173 | 011 0 174 | 010 0 175 | 001 1 176 | 000 0 177 | 178 | # 20 IFNb 179 | .n 20 0 180 | 181 | # 21 TCR 182 | .n 21 0 183 | 184 | # 22 IL18 185 | .n 22 0 186 | 187 | # 23 IL12 188 | .n 23 0 189 | 190 | .e End of file 191 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/T-Cell Signaling 2006.txt: -------------------------------------------------------------------------------- 1 | .v 40 2 | 3 | .l 1 Lck 4 | .l 2 PAGCsk 5 | .l 3 LAT 6 | .l 4 Calcin 7 | .l 5 Rsk 8 | .l 6 PLCg_bind 9 | .l 7 TCRbind 10 | .l 8 JNK 11 | .l 9 AP1 12 | .l 10 PKCth 13 | .l 11 Grb2Sos 14 | .l 12 Nfkb 15 | .l 13 IKKbeta 16 | .l 14 cCbl 17 | .l 15 Gads 18 | .l 16 Jun 19 | .l 17 SEK 20 | .l 18 Ca 21 | .l 19 Rlk 22 | .l 20 Itk 23 | .l 21 IkB 24 | .l 22 MEK 25 | .l 23 DAG 26 | .l 24 ZAP70 27 | .l 25 IP3 28 | .l 26 Fos 29 | .l 27 Raf 30 | .l 28 TCRphos 31 | .l 29 RasGRP1 32 | .l 30 PLCg_act 33 | .l 31 SLP76 34 | .l 32 Ras 35 | .l 33 NFAT 36 | .l 34 Fyn 37 | .l 35 ERK 38 | .l 36 CRE 39 | .l 37 CREB 40 | .l 38 TCRlig 41 | .l 39 CD45 42 | .l 40 CD8 43 | 44 | # 1 Lck 45 | .n 1 3 2 39 40 46 | 111 0 47 | 110 0 48 | 101 0 49 | 100 0 50 | 011 1 51 | 010 0 52 | 001 0 53 | 000 0 54 | 55 | # 2 PAGCsk 56 | .n 2 1 34 57 | 1 1 58 | 0 0 59 | 60 | # 3 LAT 61 | .n 3 1 24 62 | 1 1 63 | 0 0 64 | 65 | # 4 Calcin 66 | .n 4 1 18 67 | 1 1 68 | 0 0 69 | 70 | # 5 Rsk 71 | .n 5 1 35 72 | 1 1 73 | 0 0 74 | 75 | # 6 PLCg_bind 76 | .n 6 1 3 77 | 1 1 78 | 0 0 79 | 80 | # 7 TCRbind 81 | .n 7 2 14 38 82 | 11 0 83 | 10 0 84 | 01 1 85 | 00 0 86 | 87 | # 8 JNK 88 | .n 8 1 17 89 | 1 1 90 | 0 0 91 | 92 | # 9 AP1 93 | .n 9 2 16 26 94 | 11 1 95 | 10 0 96 | 01 0 97 | 00 0 98 | 99 | # 10 PKCth 100 | .n 10 1 23 101 | 1 1 102 | 0 0 103 | 104 | # 11 Grb2Sos 105 | .n 11 1 3 106 | 1 1 107 | 0 0 108 | 109 | # 12 Nfkb 110 | .n 12 1 21 111 | 1 0 112 | 0 1 113 | 114 | # 13 IKKbeta 115 | .n 13 1 10 116 | 1 1 117 | 0 0 118 | 119 | # 14 cCbl 120 | .n 14 1 24 121 | 1 1 122 | 0 0 123 | 124 | # 15 Gads 125 | .n 15 1 3 126 | 1 1 127 | 0 0 128 | 129 | # 16 Jun 130 | .n 16 1 8 131 | 1 1 132 | 0 0 133 | 134 | # 17 SEK 135 | .n 17 1 10 136 | 1 1 137 | 0 0 138 | 139 | # 18 Ca 140 | .n 18 1 25 141 | 1 1 142 | 0 0 143 | 144 | # 19 Rlk 145 | .n 19 1 1 146 | 1 1 147 | 0 0 148 | 149 | # 20 Itk 150 | .n 20 2 24 31 151 | 11 1 152 | 10 0 153 | 01 0 154 | 00 0 155 | 156 | # 21 IkB 157 | .n 21 1 13 158 | 1 0 159 | 0 1 160 | 161 | # 22 MEK 162 | .n 22 1 27 163 | 1 1 164 | 0 0 165 | 166 | # 23 DAG 167 | .n 23 1 30 168 | 1 1 169 | 0 0 170 | 171 | # 24 ZAP70 172 | .n 24 3 1 14 28 173 | 111 0 174 | 110 0 175 | 101 1 176 | 100 0 177 | 011 0 178 | 010 0 179 | 001 0 180 | 000 0 181 | 182 | # 25 IP3 183 | .n 25 1 30 184 | 1 1 185 | 0 0 186 | 187 | # 26 Fos 188 | .n 26 1 35 189 | 1 1 190 | 0 0 191 | 192 | # 27 Raf 193 | .n 27 1 32 194 | 1 1 195 | 0 0 196 | 197 | # 28 TCRphos 198 | .n 28 1 34 199 | 1 1 200 | 0 0 201 | 202 | # 29 RasGRP1 203 | .n 29 2 10 23 204 | 11 1 205 | 10 0 206 | 01 0 207 | 00 0 208 | 209 | # 30 PLCg_act 210 | .n 30 5 6 19 20 24 31 211 | 11111 1 212 | 11110 0 213 | 11101 0 214 | 11100 0 215 | 11011 1 216 | 11010 0 217 | 11001 0 218 | 11000 0 219 | 10111 1 220 | 10110 0 221 | 10101 0 222 | 10100 0 223 | 10011 0 224 | 10010 0 225 | 10001 0 226 | 10000 0 227 | 01111 0 228 | 01110 0 229 | 01101 0 230 | 01100 0 231 | 01011 0 232 | 01010 0 233 | 01001 0 234 | 01000 0 235 | 00111 0 236 | 00110 0 237 | 00101 0 238 | 00100 0 239 | 00011 0 240 | 00010 0 241 | 00001 0 242 | 00000 0 243 | 244 | # 31 SLP76 245 | .n 31 1 15 246 | 1 1 247 | 0 0 248 | 249 | # 32 Ras 250 | .n 32 2 11 29 251 | 11 1 252 | 10 1 253 | 01 1 254 | 00 0 255 | 256 | # 33 NFAT 257 | .n 33 1 4 258 | 1 1 259 | 0 0 260 | 261 | # 34 Fyn 262 | .n 34 3 1 7 39 263 | 111 1 264 | 110 0 265 | 101 1 266 | 100 0 267 | 011 1 268 | 010 0 269 | 001 0 270 | 000 0 271 | 272 | # 35 ERK 273 | .n 35 1 22 274 | 1 1 275 | 0 0 276 | 277 | # 36 CRE 278 | .n 36 1 37 279 | 1 1 280 | 0 0 281 | 282 | # 37 CREB 283 | .n 37 1 5 284 | 1 1 285 | 0 0 286 | 287 | # 38 TCRlig 288 | .n 38 0 289 | 290 | # 39 CD45 291 | .n 39 0 292 | 293 | # 40 CD8 294 | .n 40 0 295 | 296 | .e End of file 297 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/T-LGL Survival Network 2011 Reduced Network.txt: -------------------------------------------------------------------------------- 1 | .v 18 2 | 3 | .l 1 Ceramide 4 | .l 2 GPCR 5 | .l 3 sFas 6 | .l 4 P2 7 | .l 5 SMAD 8 | .l 6 BID 9 | .l 7 CTLA4 10 | .l 8 IFNG 11 | .l 9 S1P 12 | .l 10 MCL1 13 | .l 11 Fas 14 | .l 12 TCR 15 | .l 13 Caspase 16 | .l 14 IAP 17 | .l 15 FLIP 18 | .l 16 DISC 19 | .l 17 CREB 20 | .l 18 Apoptosis 21 | 22 | # 1 Ceramide 23 | .n 1 3 9 11 18 24 | 111 0 25 | 110 0 26 | 101 0 27 | 100 0 28 | 011 0 29 | 010 1 30 | 001 0 31 | 000 0 32 | 33 | # 2 GPCR 34 | .n 2 2 9 18 35 | 11 0 36 | 10 1 37 | 01 0 38 | 00 0 39 | 40 | # 3 sFas 41 | .n 3 2 9 18 42 | 11 0 43 | 10 1 44 | 01 0 45 | 00 0 46 | 47 | # 4 P2 48 | .n 4 3 4 8 18 49 | 111 0 50 | 110 1 51 | 101 0 52 | 100 1 53 | 011 0 54 | 010 1 55 | 001 0 56 | 000 0 57 | 58 | # 5 SMAD 59 | .n 5 2 2 18 60 | 11 0 61 | 10 1 62 | 01 0 63 | 00 0 64 | 65 | # 6 BID 66 | .n 6 2 10 18 67 | 11 0 68 | 10 0 69 | 01 0 70 | 00 1 71 | 72 | # 7 CTLA4 73 | .n 7 2 12 18 74 | 11 0 75 | 10 1 76 | 01 0 77 | 00 0 78 | 79 | # 8 IFNG 80 | .n 8 3 4 5 18 81 | 111 0 82 | 110 0 83 | 101 0 84 | 100 0 85 | 011 0 86 | 010 0 87 | 001 0 88 | 000 1 89 | 90 | # 9 S1P 91 | .n 9 2 1 18 92 | 11 0 93 | 10 0 94 | 01 0 95 | 00 1 96 | 97 | # 10 MCL1 98 | .n 10 2 16 18 99 | 11 0 100 | 10 0 101 | 01 0 102 | 00 1 103 | 104 | # 11 Fas 105 | .n 11 2 3 18 106 | 11 0 107 | 10 0 108 | 01 0 109 | 00 1 110 | 111 | # 12 TCR 112 | .n 12 2 7 18 113 | 11 0 114 | 10 0 115 | 01 0 116 | 00 1 117 | 118 | # 13 Caspase 119 | .n 13 4 6 14 16 18 120 | 1111 0 121 | 1110 1 122 | 1101 0 123 | 1100 0 124 | 1011 0 125 | 1010 1 126 | 1001 0 127 | 1000 1 128 | 0111 0 129 | 0110 1 130 | 0101 0 131 | 0100 0 132 | 0011 0 133 | 0010 1 134 | 0001 0 135 | 0000 0 136 | 137 | # 14 IAP 138 | .n 14 2 6 18 139 | 11 0 140 | 10 0 141 | 01 0 142 | 00 1 143 | 144 | # 15 FLIP 145 | .n 15 2 16 18 146 | 11 0 147 | 10 0 148 | 01 0 149 | 00 1 150 | 151 | # 16 DISC 152 | .n 16 4 1 11 15 18 153 | 1111 0 154 | 1110 1 155 | 1101 0 156 | 1100 1 157 | 1011 0 158 | 1010 1 159 | 1001 0 160 | 1000 1 161 | 0111 0 162 | 0110 0 163 | 0101 0 164 | 0100 1 165 | 0011 0 166 | 0010 0 167 | 0001 0 168 | 0000 0 169 | 170 | # 17 CREB 171 | .n 17 2 8 18 172 | 11 0 173 | 10 1 174 | 01 0 175 | 00 0 176 | 177 | # 18 Apoptosis 178 | .n 18 2 13 18 179 | 11 1 180 | 10 1 181 | 01 1 182 | 00 0 183 | 184 | .e End of file 185 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Toll Pathway of Drosophila Signaling Pathway.txt: -------------------------------------------------------------------------------- 1 | .v 11 2 | 3 | .l 1 Spz 4 | .l 2 MyD88 5 | .l 3 Tube 6 | .l 4 Pelle 7 | .l 5 Cactus 8 | .l 6 Toll 9 | .l 7 Targets 10 | .l 8 Dorsal 11 | .l 9 Dif 12 | .l 10 Nec 13 | .l 11 Slmb 14 | 15 | # 1 Spz 16 | .n 1 1 10 17 | 1 0 18 | 0 1 19 | 20 | # 2 MyD88 21 | .n 2 1 6 22 | 1 1 23 | 0 0 24 | 25 | # 3 Tube 26 | .n 3 1 2 27 | 1 1 28 | 0 0 29 | 30 | # 4 Pelle 31 | .n 4 1 3 32 | 1 1 33 | 0 0 34 | 35 | # 5 Cactus 36 | .n 5 2 4 11 37 | 11 0 38 | 10 1 39 | 01 1 40 | 00 1 41 | 42 | # 6 Toll 43 | .n 6 1 1 44 | 1 1 45 | 0 0 46 | 47 | # 7 Targets 48 | .n 7 2 8 9 49 | 11 1 50 | 10 1 51 | 01 1 52 | 00 0 53 | 54 | # 8 Dorsal 55 | .n 8 1 5 56 | 1 0 57 | 0 1 58 | 59 | # 9 Dif 60 | .n 9 1 5 61 | 1 0 62 | 0 1 63 | 64 | # 10 Nec 65 | .n 10 0 66 | 67 | # 11 Slmb 68 | .n 11 0 69 | 70 | .e End of file 71 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Treatment of Castration-Resistant Prostate Cancer.txt: -------------------------------------------------------------------------------- 1 | .v 42 2 | 3 | .l 1 Raf 4 | .l 2 IRS1 5 | .l 3 mTOR 6 | .l 4 SP1 7 | .l 5 BAD 8 | .l 6 PSA 9 | .l 7 EGFR/ERBB2 10 | .l 8 PDPK1 11 | .l 9 TMPRSS2 12 | .l 10 TSC_1/2 13 | .l 11 RP6SKB1 14 | .l 12 GRB2/SOS 15 | .l 13 AR/AR 16 | .l 14 p21 17 | .l 15 AKT 18 | .l 16 RHEB 19 | .l 17 ERK1/2 20 | .l 18 IGFR1A/B 21 | .l 19 ERBB2/3 22 | .l 20 MEK1 23 | .l 21 PIK3CA 24 | .l 22 PIP3 25 | .l 23 SRF-ELK1 26 | .l 24 BCL2 27 | .l 25 AR/HSP 28 | .l 26 EFGR 29 | .l 27 Ras 30 | .l 28 CDK2-Cyclin_E 31 | .l 29 AZD6244 32 | .l 30 IGF 33 | .l 31 Temsirolimus 34 | .l 32 NRG1 35 | .l 33 PTEN 36 | .l 34 NKX3.1 37 | .l 35 Lapatinib 38 | .l 36 Cixutumumab 39 | .l 37 EGF 40 | .l 38 BKM120 41 | .l 39 AZD5363 42 | .l 40 Enzalutamide 43 | .l 41 Androgens 44 | .l 42 HBEGF 45 | 46 | # 1 Raf 47 | .n 1 3 21 27 38 48 | 111 1 49 | 110 1 50 | 101 0 51 | 100 1 52 | 011 1 53 | 010 1 54 | 001 0 55 | 000 0 56 | 57 | # 2 IRS1 58 | .n 2 2 18 36 59 | 11 0 60 | 10 1 61 | 01 0 62 | 00 0 63 | 64 | # 3 mTOR 65 | .n 3 1 16 66 | 1 1 67 | 0 0 68 | 69 | # 4 SP1 70 | .n 4 1 17 71 | 1 1 72 | 0 0 73 | 74 | # 5 BAD 75 | .n 5 2 11 15 76 | 11 0 77 | 10 0 78 | 01 0 79 | 00 1 80 | 81 | # 6 PSA 82 | .n 6 2 13 40 83 | 11 0 84 | 10 1 85 | 01 0 86 | 00 0 87 | 88 | # 7 EGFR/ERBB2 89 | .n 7 1 37 90 | 1 1 91 | 0 0 92 | 93 | # 8 PDPK1 94 | .n 8 1 22 95 | 1 1 96 | 0 0 97 | 98 | # 9 TMPRSS2 99 | .n 9 2 13 40 100 | 11 0 101 | 10 1 102 | 01 0 103 | 00 0 104 | 105 | # 10 TSC_1/2 106 | .n 10 2 15 39 107 | 11 1 108 | 10 0 109 | 01 1 110 | 00 1 111 | 112 | # 11 RP6SKB1 113 | .n 11 4 3 8 17 31 114 | 1111 1 115 | 1110 1 116 | 1101 1 117 | 1100 1 118 | 1011 1 119 | 1010 1 120 | 1001 0 121 | 1000 1 122 | 0111 1 123 | 0110 1 124 | 0101 1 125 | 0100 1 126 | 0011 1 127 | 0010 1 128 | 0001 0 129 | 0000 0 130 | 131 | # 12 GRB2/SOS 132 | .n 12 5 7 18 19 26 35 133 | 11111 1 134 | 11110 1 135 | 11101 1 136 | 11100 1 137 | 11011 1 138 | 11010 1 139 | 11001 1 140 | 11000 1 141 | 10111 0 142 | 10110 1 143 | 10101 0 144 | 10100 1 145 | 10011 0 146 | 10010 1 147 | 10001 0 148 | 10000 1 149 | 01111 1 150 | 01110 1 151 | 01101 1 152 | 01100 1 153 | 01011 1 154 | 01010 1 155 | 01001 1 156 | 01000 1 157 | 00111 0 158 | 00110 1 159 | 00101 0 160 | 00100 1 161 | 00011 0 162 | 00010 1 163 | 00001 0 164 | 00000 0 165 | 166 | # 13 AR/AR 167 | .n 13 2 15 25 168 | 11 1 169 | 10 1 170 | 01 1 171 | 00 0 172 | 173 | # 14 p21 174 | .n 14 1 15 175 | 1 0 176 | 0 1 177 | 178 | # 15 AKT 179 | .n 15 3 8 33 34 180 | 111 1 181 | 110 1 182 | 101 1 183 | 100 1 184 | 011 0 185 | 010 1 186 | 001 1 187 | 000 1 188 | 189 | # 16 RHEB 190 | .n 16 1 10 191 | 1 0 192 | 0 1 193 | 194 | # 17 ERK1/2 195 | .n 17 2 20 29 196 | 11 0 197 | 10 1 198 | 01 0 199 | 00 0 200 | 201 | # 18 IGFR1A/B 202 | .n 18 1 30 203 | 1 1 204 | 0 0 205 | 206 | # 19 ERBB2/3 207 | .n 19 1 32 208 | 1 1 209 | 0 0 210 | 211 | # 20 MEK1 212 | .n 20 1 1 213 | 1 1 214 | 0 0 215 | 216 | # 21 PIK3CA 217 | .n 21 3 2 19 27 218 | 111 1 219 | 110 1 220 | 101 1 221 | 100 1 222 | 011 1 223 | 010 1 224 | 001 1 225 | 000 0 226 | 227 | # 22 PIP3 228 | .n 22 2 21 33 229 | 11 0 230 | 10 1 231 | 01 0 232 | 00 0 233 | 234 | # 23 SRF-ELK1 235 | .n 23 2 11 17 236 | 11 1 237 | 10 0 238 | 01 0 239 | 00 0 240 | 241 | # 24 BCL2 242 | .n 24 1 5 243 | 1 0 244 | 0 1 245 | 246 | # 25 AR/HSP 247 | .n 25 1 41 248 | 1 1 249 | 0 0 250 | 251 | # 26 EFGR 252 | .n 26 2 37 42 253 | 11 1 254 | 10 1 255 | 01 1 256 | 00 0 257 | 258 | # 27 Ras 259 | .n 27 1 12 260 | 1 1 261 | 0 0 262 | 263 | # 28 CDK2-Cyclin_E 264 | .n 28 1 14 265 | 1 0 266 | 0 1 267 | 268 | # 29 AZD6244 269 | .n 29 0 270 | 271 | # 30 IGF 272 | .n 30 0 273 | 274 | # 31 Temsirolimus 275 | .n 31 0 276 | 277 | # 32 NRG1 278 | .n 32 0 279 | 280 | # 33 PTEN 281 | .n 33 0 282 | 283 | # 34 NKX3.1 284 | .n 34 0 285 | 286 | # 35 Lapatinib 287 | .n 35 0 288 | 289 | # 36 Cixutumumab 290 | .n 36 0 291 | 292 | # 37 EGF 293 | .n 37 0 294 | 295 | # 38 BKM120 296 | .n 38 0 297 | 298 | # 39 AZD5363 299 | .n 39 0 300 | 301 | # 40 Enzalutamide 302 | .n 40 0 303 | 304 | # 41 Androgens 305 | .n 41 0 306 | 307 | # 42 HBEGF 308 | .n 42 0 309 | 310 | .e End of file 311 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Trichostrongylus retortaeformis.txt: -------------------------------------------------------------------------------- 1 | .v 26 2 | 3 | .l 1 IL5 4 | .l 2 IgE 5 | .l 3 Th2II 6 | .l 4 DCI 7 | .l 5 DCII 8 | .l 6 IFNgI 9 | .l 7 Th1I 10 | .l 8 IL12II 11 | .l 9 EL 12 | .l 10 IgG 13 | .l 11 Th2I 14 | .l 12 IL4I 15 | .l 13 IL10I 16 | .l 14 TEL 17 | .l 15 AD 18 | .l 16 IL13 19 | .l 17 BC 20 | .l 18 PIC 21 | .l 19 NE 22 | .l 20 EL2 23 | .l 21 IL4II 24 | .l 22 Th1II 25 | .l 23 EC 26 | .l 24 IgA 27 | .l 25 T0 28 | .l 26 IS 29 | 30 | # 1 IL5 31 | .n 1 2 11 20 32 | 11 1 33 | 10 1 34 | 01 1 35 | 00 0 36 | 37 | # 2 IgE 38 | .n 2 3 16 17 21 39 | 111 1 40 | 110 1 41 | 101 0 42 | 100 0 43 | 011 1 44 | 010 0 45 | 001 0 46 | 000 0 47 | 48 | # 3 Th2II 49 | .n 3 3 5 8 25 50 | 111 0 51 | 110 0 52 | 101 1 53 | 100 0 54 | 011 0 55 | 010 0 56 | 001 0 57 | 000 0 58 | 59 | # 4 DCI 60 | .n 4 1 18 61 | 1 1 62 | 0 0 63 | 64 | # 5 DCII 65 | .n 5 1 4 66 | 1 1 67 | 0 0 68 | 69 | # 6 IFNgI 70 | .n 6 2 4 7 71 | 11 1 72 | 10 1 73 | 01 1 74 | 00 0 75 | 76 | # 7 Th1I 77 | .n 7 1 22 78 | 1 1 79 | 0 0 80 | 81 | # 8 IL12II 82 | .n 8 3 5 21 25 83 | 111 0 84 | 110 0 85 | 101 1 86 | 100 0 87 | 011 0 88 | 010 0 89 | 001 0 90 | 000 0 91 | 92 | # 9 EL 93 | .n 9 2 20 26 94 | 11 0 95 | 10 0 96 | 01 1 97 | 00 0 98 | 99 | # 10 IgG 100 | .n 10 1 17 101 | 1 1 102 | 0 0 103 | 104 | # 11 Th2I 105 | .n 11 1 3 106 | 1 1 107 | 0 0 108 | 109 | # 12 IL4I 110 | .n 12 1 21 111 | 1 1 112 | 0 0 113 | 114 | # 13 IL10I 115 | .n 13 1 11 116 | 1 1 117 | 0 0 118 | 119 | # 14 TEL 120 | .n 14 2 9 20 121 | 11 1 122 | 10 1 123 | 01 1 124 | 00 0 125 | 126 | # 15 AD 127 | .n 15 4 10 15 19 26 128 | 1111 0 129 | 1110 0 130 | 1101 1 131 | 1100 1 132 | 1011 0 133 | 1010 0 134 | 1001 1 135 | 1000 0 136 | 0111 1 137 | 0110 1 138 | 0101 1 139 | 0100 1 140 | 0011 1 141 | 0010 0 142 | 0001 1 143 | 0000 0 144 | 145 | # 16 IL13 146 | .n 16 4 9 11 20 26 147 | 1111 1 148 | 1110 1 149 | 1101 1 150 | 1100 1 151 | 1011 1 152 | 1010 1 153 | 1001 1 154 | 1000 0 155 | 0111 1 156 | 0110 1 157 | 0101 1 158 | 0100 1 159 | 0011 1 160 | 0010 1 161 | 0001 0 162 | 0000 0 163 | 164 | # 17 BC 165 | .n 17 2 17 25 166 | 11 1 167 | 10 1 168 | 01 1 169 | 00 0 170 | 171 | # 18 PIC 172 | .n 18 3 13 23 24 173 | 111 0 174 | 110 0 175 | 101 0 176 | 100 0 177 | 011 0 178 | 010 1 179 | 001 0 180 | 000 0 181 | 182 | # 19 NE 183 | .n 19 5 6 12 13 15 18 184 | 11111 0 185 | 11110 0 186 | 11101 0 187 | 11100 0 188 | 11011 0 189 | 11010 0 190 | 11001 0 191 | 11000 0 192 | 10111 0 193 | 10110 0 194 | 10101 0 195 | 10100 0 196 | 10011 1 197 | 10010 1 198 | 10001 1 199 | 10000 1 200 | 01111 0 201 | 01110 0 202 | 01101 0 203 | 01100 0 204 | 01011 0 205 | 01010 0 206 | 01001 0 207 | 01000 0 208 | 00111 0 209 | 00110 0 210 | 00101 0 211 | 00100 0 212 | 00011 1 213 | 00010 0 214 | 00001 0 215 | 00000 0 216 | 217 | # 20 EL2 218 | .n 20 3 1 2 16 219 | 111 1 220 | 110 1 221 | 101 1 222 | 100 0 223 | 011 0 224 | 010 0 225 | 001 0 226 | 000 0 227 | 228 | # 21 IL4II 229 | .n 21 5 3 5 8 20 25 230 | 11111 1 231 | 11110 1 232 | 11101 0 233 | 11100 0 234 | 11011 1 235 | 11010 1 236 | 11001 1 237 | 11000 1 238 | 10111 1 239 | 10110 1 240 | 10101 0 241 | 10100 0 242 | 10011 1 243 | 10010 1 244 | 10001 1 245 | 10000 1 246 | 01111 1 247 | 01110 1 248 | 01101 0 249 | 01100 0 250 | 01011 1 251 | 01010 1 252 | 01001 1 253 | 01000 0 254 | 00111 1 255 | 00110 1 256 | 00101 0 257 | 00100 0 258 | 00011 1 259 | 00010 1 260 | 00001 0 261 | 00000 0 262 | 263 | # 22 Th1II 264 | .n 22 3 5 8 25 265 | 111 1 266 | 110 0 267 | 101 0 268 | 100 0 269 | 011 0 270 | 010 0 271 | 001 0 272 | 000 0 273 | 274 | # 23 EC 275 | .n 23 2 15 26 276 | 11 1 277 | 10 1 278 | 01 1 279 | 00 0 280 | 281 | # 24 IgA 282 | .n 24 2 17 26 283 | 11 1 284 | 10 0 285 | 01 0 286 | 00 0 287 | 288 | # 25 T0 289 | .n 25 1 5 290 | 1 1 291 | 0 0 292 | 293 | # 26 IS 294 | .n 26 0 295 | 296 | .e End of file 297 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/VEGF Pathway of Drosophila Signaling Pathway.txt: -------------------------------------------------------------------------------- 1 | .v 18 2 | 3 | .l 1 Rl 4 | .l 2 Targets 5 | .l 3 Raf 6 | .l 4 Ras 7 | .l 5 Pvr 8 | .l 6 Pnt 9 | .l 7 Drk 10 | .l 8 Dsor1 11 | .l 9 Sos 12 | .l 10 Aop 13 | .l 11 Src42 14 | .l 12 msk 15 | .l 13 Pvf1 16 | .l 14 Pvf2 17 | .l 15 CNK 18 | .l 16 Sty 19 | .l 17 Pvf3 20 | .l 18 Ksr 21 | 22 | # 1 Rl 23 | .n 1 2 8 12 24 | 11 1 25 | 10 0 26 | 01 0 27 | 00 0 28 | 29 | # 2 Targets 30 | .n 2 2 6 10 31 | 11 0 32 | 10 1 33 | 01 0 34 | 00 0 35 | 36 | # 3 Raf 37 | .n 3 4 4 11 15 18 38 | 1111 1 39 | 1110 0 40 | 1101 0 41 | 1100 0 42 | 1011 0 43 | 1010 0 44 | 1001 0 45 | 1000 0 46 | 0111 0 47 | 0110 0 48 | 0101 0 49 | 0100 0 50 | 0011 0 51 | 0010 0 52 | 0001 0 53 | 0000 0 54 | 55 | # 4 Ras 56 | .n 4 2 9 16 57 | 11 0 58 | 10 1 59 | 01 0 60 | 00 0 61 | 62 | # 5 Pvr 63 | .n 5 3 13 14 17 64 | 111 1 65 | 110 1 66 | 101 1 67 | 100 1 68 | 011 1 69 | 010 1 70 | 001 1 71 | 000 0 72 | 73 | # 6 Pnt 74 | .n 6 1 1 75 | 1 1 76 | 0 0 77 | 78 | # 7 Drk 79 | .n 7 1 5 80 | 1 1 81 | 0 0 82 | 83 | # 8 Dsor1 84 | .n 8 1 3 85 | 1 1 86 | 0 0 87 | 88 | # 9 Sos 89 | .n 9 1 7 90 | 1 1 91 | 0 0 92 | 93 | # 10 Aop 94 | .n 10 1 1 95 | 1 0 96 | 0 1 97 | 98 | # 11 Src42 99 | .n 11 0 100 | 101 | # 12 msk 102 | .n 12 0 103 | 104 | # 13 Pvf1 105 | .n 13 0 106 | 107 | # 14 Pvf2 108 | .n 14 0 109 | 110 | # 15 CNK 111 | .n 15 0 112 | 113 | # 16 Sty 114 | .n 16 0 115 | 116 | # 17 Pvf3 117 | .n 17 0 118 | 119 | # 18 Ksr 120 | .n 18 0 121 | 122 | .e End of file 123 | -------------------------------------------------------------------------------- /cana/datasets/cell_collective/Wg Pathway of Drosophila Signalling Pathways.txt: -------------------------------------------------------------------------------- 1 | .v 26 2 | 3 | .l 1 Pan 4 | .l 2 Axin 5 | .l 3 Dlp 6 | .l 4 Arr 7 | .l 5 Dsh 8 | .l 6 Nemo 9 | .l 7 Targets 10 | .l 8 Arm 11 | .l 9 Sgg 12 | .l 10 Fz 13 | .l 11 APC 14 | .l 12 Dally 15 | .l 13 Hyx 16 | .l 14 Wf 17 | .l 15 Proteasome 18 | .l 16 Gro 19 | .l 17 Nkd 20 | .l 18 Hipk 21 | .l 19 Boca 22 | .l 20 Nej 23 | .l 21 Wg 24 | .l 22 CK1alpha 25 | .l 23 Ttv 26 | .l 24 Lgs 27 | .l 25 Slmb 28 | .l 26 Pygo 29 | 30 | # 1 Pan 31 | .n 1 2 6 8 32 | 11 0 33 | 10 0 34 | 01 1 35 | 00 0 36 | 37 | # 2 Axin 38 | .n 2 1 5 39 | 1 0 40 | 0 1 41 | 42 | # 3 Dlp 43 | .n 3 2 14 23 44 | 11 0 45 | 10 0 46 | 01 1 47 | 00 0 48 | 49 | # 4 Arr 50 | .n 4 1 21 51 | 1 1 52 | 0 0 53 | 54 | # 5 Dsh 55 | .n 5 3 4 10 17 56 | 111 0 57 | 110 1 58 | 101 0 59 | 100 1 60 | 011 0 61 | 010 1 62 | 001 0 63 | 000 0 64 | 65 | # 6 Nemo 66 | .n 6 1 1 67 | 1 1 68 | 0 0 69 | 70 | # 7 Targets 71 | .n 7 6 1 13 16 20 24 26 72 | 111111 0 73 | 111110 0 74 | 111101 0 75 | 111100 0 76 | 111011 0 77 | 111010 0 78 | 111001 0 79 | 111000 0 80 | 110111 1 81 | 110110 0 82 | 110101 0 83 | 110100 0 84 | 110011 0 85 | 110010 0 86 | 110001 0 87 | 110000 0 88 | 101111 0 89 | 101110 0 90 | 101101 0 91 | 101100 0 92 | 101011 0 93 | 101010 0 94 | 101001 0 95 | 101000 0 96 | 100111 0 97 | 100110 0 98 | 100101 0 99 | 100100 0 100 | 100011 0 101 | 100010 0 102 | 100001 0 103 | 100000 0 104 | 011111 0 105 | 011110 0 106 | 011101 0 107 | 011100 0 108 | 011011 0 109 | 011010 0 110 | 011001 0 111 | 011000 0 112 | 010111 0 113 | 010110 0 114 | 010101 0 115 | 010100 0 116 | 010011 0 117 | 010010 0 118 | 010001 0 119 | 010000 0 120 | 001111 0 121 | 001110 0 122 | 001101 0 123 | 001100 0 124 | 001011 0 125 | 001010 0 126 | 001001 0 127 | 001000 0 128 | 000111 0 129 | 000110 0 130 | 000101 0 131 | 000100 0 132 | 000011 0 133 | 000010 0 134 | 000001 0 135 | 000000 0 136 | 137 | # 8 Arm 138 | .n 8 7 2 9 11 15 18 22 25 139 | 1111111 0 140 | 1111110 1 141 | 1111101 0 142 | 1111100 0 143 | 1111011 0 144 | 1111010 0 145 | 1111001 0 146 | 1111000 0 147 | 1110111 1 148 | 1110110 1 149 | 1110101 0 150 | 1110100 0 151 | 1110011 0 152 | 1110010 0 153 | 1110001 0 154 | 1110000 0 155 | 1101111 1 156 | 1101110 1 157 | 1101101 0 158 | 1101100 0 159 | 1101011 0 160 | 1101010 0 161 | 1101001 0 162 | 1101000 0 163 | 1100111 1 164 | 1100110 1 165 | 1100101 0 166 | 1100100 0 167 | 1100011 0 168 | 1100010 0 169 | 1100001 0 170 | 1100000 0 171 | 1011111 1 172 | 1011110 1 173 | 1011101 0 174 | 1011100 0 175 | 1011011 0 176 | 1011010 0 177 | 1011001 0 178 | 1011000 0 179 | 1010111 1 180 | 1010110 1 181 | 1010101 0 182 | 1010100 0 183 | 1010011 0 184 | 1010010 0 185 | 1010001 0 186 | 1010000 0 187 | 1001111 1 188 | 1001110 1 189 | 1001101 0 190 | 1001100 0 191 | 1001011 0 192 | 1001010 0 193 | 1001001 0 194 | 1001000 0 195 | 1000111 1 196 | 1000110 1 197 | 1000101 0 198 | 1000100 0 199 | 1000011 0 200 | 1000010 0 201 | 1000001 0 202 | 1000000 0 203 | 0111111 1 204 | 0111110 1 205 | 0111101 0 206 | 0111100 0 207 | 0111011 0 208 | 0111010 0 209 | 0111001 0 210 | 0111000 0 211 | 0110111 1 212 | 0110110 1 213 | 0110101 0 214 | 0110100 0 215 | 0110011 0 216 | 0110010 0 217 | 0110001 0 218 | 0110000 0 219 | 0101111 1 220 | 0101110 1 221 | 0101101 0 222 | 0101100 0 223 | 0101011 0 224 | 0101010 0 225 | 0101001 0 226 | 0101000 0 227 | 0100111 1 228 | 0100110 1 229 | 0100101 0 230 | 0100100 0 231 | 0100011 0 232 | 0100010 0 233 | 0100001 0 234 | 0100000 0 235 | 0011111 1 236 | 0011110 1 237 | 0011101 0 238 | 0011100 0 239 | 0011011 0 240 | 0011010 0 241 | 0011001 0 242 | 0011000 0 243 | 0010111 1 244 | 0010110 1 245 | 0010101 0 246 | 0010100 0 247 | 0010011 0 248 | 0010010 0 249 | 0010001 0 250 | 0010000 0 251 | 0001111 1 252 | 0001110 1 253 | 0001101 0 254 | 0001100 0 255 | 0001011 0 256 | 0001010 0 257 | 0001001 0 258 | 0001000 0 259 | 0000111 1 260 | 0000110 1 261 | 0000101 0 262 | 0000100 0 263 | 0000011 0 264 | 0000010 0 265 | 0000001 0 266 | 0000000 0 267 | 268 | # 9 Sgg 269 | .n 9 1 5 270 | 1 0 271 | 0 1 272 | 273 | # 10 Fz 274 | .n 10 2 19 21 275 | 11 1 276 | 10 0 277 | 01 0 278 | 00 0 279 | 280 | # 11 APC 281 | .n 11 1 5 282 | 1 0 283 | 0 1 284 | 285 | # 12 Dally 286 | .n 12 2 14 23 287 | 11 0 288 | 10 0 289 | 01 1 290 | 00 0 291 | 292 | # 13 Hyx 293 | .n 13 0 294 | 295 | # 14 Wf 296 | .n 14 0 297 | 298 | # 15 Proteasome 299 | .n 15 0 300 | 301 | # 16 Gro 302 | .n 16 0 303 | 304 | # 17 Nkd 305 | .n 17 0 306 | 307 | # 18 Hipk 308 | .n 18 0 309 | 310 | # 19 Boca 311 | .n 19 0 312 | 313 | # 20 Nej 314 | .n 20 0 315 | 316 | # 21 Wg 317 | .n 21 0 318 | 319 | # 22 CK1alpha 320 | .n 22 0 321 | 322 | # 23 Ttv 323 | .n 23 0 324 | 325 | # 24 Lgs 326 | .n 24 0 327 | 328 | # 25 Slmb 329 | .n 25 0 330 | 331 | # 26 Pygo 332 | .n 26 0 333 | 334 | .e End of file 335 | -------------------------------------------------------------------------------- /cana/datasets/drosophila_single_cell.txt: -------------------------------------------------------------------------------- 1 | #total number of nodes 2 | .v 17 3 | 4 | # labels of nodes and names of corresponding components 5 | .l 1 SLP 6 | .l 2 wg 7 | .l 3 WG 8 | .l 4 en 9 | .l 5 EN 10 | .l 6 hh 11 | .l 7 HH 12 | .l 8 ptc 13 | .l 9 PTC 14 | .l 10 PH 15 | .l 11 SMO 16 | .l 12 ci 17 | .l 13 CI 18 | .l 14 CIA 19 | .l 15 CIR 20 | .l 16 nhhnHH 21 | .l 17 nWG 22 | 23 | # 1 = SLP 24 | .n 1 0 25 | 26 | # 2 = wg 27 | .n 2 4 1 2 14 15 28 | 1010 1 29 | 1110 1 30 | 1110 1 31 | 0110 1 32 | 1100 1 33 | 34 | # 3 = WG 35 | .n 3 1 2 36 | 1 1 37 | 38 | # 4 = en 39 | .n 4 2 1 17 40 | 01 1 41 | 42 | # 5 = EN 43 | .n 5 1 4 44 | 1 1 45 | 46 | # 6 = hh 47 | .n 6 2 5 15 48 | 10 1 49 | 50 | # 7 = HH 51 | .n 7 1 6 52 | 1 1 53 | 54 | # 8 = ptc 55 | .n 8 3 5 14 15 56 | 010 1 57 | 58 | # 9 = PTC 59 | .n 9 3 8 9 16 60 | 100 1 61 | 101 1 62 | 110 1 63 | 111 1 64 | 010 1 65 | 66 | # 10 = PH 67 | .n 10 2 9 16 68 | 11 1 69 | 70 | # 11 = SMO 71 | .n 11 2 9 16 72 | 00 1 73 | 01 1 74 | 11 1 75 | 76 | # 12 = ci 77 | .n 12 1 5 78 | 0 1 79 | 80 | # 13 = CI 81 | .n 13 1 12 82 | 1 1 83 | 84 | # 14 = CIA 85 | .n 14 3 9 13 16 86 | 010 1 87 | 011 1 88 | 111 1 89 | 90 | # 15 = CIR 91 | .n 15 3 9 13 16 92 | 110 1 93 | 94 | # 16 = nhh/nHH 95 | .n 16 0 96 | 97 | 98 | # 17 = nWG 99 | .n 17 0 100 | 101 | 102 | .e End of file 103 | #.n (node number) (in-degree) (input node 1) … (input node k) 104 | # - is a wild-card 105 | 106 | 107 | -------------------------------------------------------------------------------- /cana/datasets/leukemia.txt: -------------------------------------------------------------------------------- 1 | #Boolean network model of survival signaling in T-LGL leukemia 2 | #From Zhang, Ranran, et al. 3 | #"Network model of survival signaling in large granular lymphocyte leukemia." 4 | #Proceedings of the National Academy of Sciences 105.42 (2008): 16308-16313. 5 | #BOOLEAN RULES 6 | CTLA4* =TCR 7 | TCR*= Stimuli and not CTLA4 8 | PDGFR *=S1P or PDGF 9 | FYN *= TCR or IL2RB 10 | Cytoskeleton_signaling*= FYN 11 | LCK * =CD45 or ((TCR or IL2RB) and not ZAP70) 12 | ZAP70*= LCK and not FYN 13 | GRB2*= IL2RB or ZAP70 14 | PLCG1*=GRB2 or PDGFR 15 | RAS*=(GRB2 or PLCG1) and not GAP 16 | GAP*=(RAS or (PDGFR and GAP)) and not (IL15 or IL2) 17 | MEK*=RAS 18 | ERK*=MEK and PI3K 19 | PI3K*=PDGFR or RAS 20 | NFKB*=(TPL2 or PI3K) or (FLIP and TRADD and IAP) 21 | NFAT*=PI3K 22 | RANTES*=NFKB 23 | IL2*=(NFKB or STAT3 or NFAT) and not TBET 24 | IL2RBT*=ERK and TBET 25 | IL2RB*=IL2RBT and (IL2 or IL15) 26 | IL2RAT*=IL2 and (STAT3 or NFKB) 27 | IL2RA*=(IL2 and IL2RAT) and not IL2RA 28 | JAK*=(IL2RA or IL2RB or RANTES or IFNG) and not (SOCS or CD45) 29 | SOCS*=JAK and not (IL2 or IL15) 30 | STAT3*=JAK 31 | P27*=STAT3 32 | Proliferation*=STAT3 and not P27 33 | TBET*=JAK or TBET 34 | CREB*=ERK and IFNG 35 | IFNGT*=TBET or STAT3 or NFAT 36 | IFNG*=((IL2 or IL15 or Stimuli) and IFNGT) and not (SMAD or P2) 37 | P2*=(IFNG or P2) and not Stimuli2 38 | GZMB*=(CREB and IFNG) or TBET 39 | TPL2*=TAX or (PI3K and TNF) 40 | TNF*=NFKB 41 | TRADD*=TNF and not (IAP or A20) 42 | FasL*=STAT3 or NFKB or NFAT or ERK 43 | FasT*=NFKB 44 | Fas*=(FasT and FasL) and not sFas 45 | sFas*=FasT and S1P 46 | Ceramide*=Fas and not S1P 47 | DISC*=FasT and ((Fas and IL2) or Ceramide or (Fas and not FLIP)) 48 | Caspase*=(((TRADD or GZMB) and BID) and not IAP) or DISC 49 | FLIP*=(NFKB or (CREB and IFNG)) and not DISC 50 | A20*=NFKB 51 | BID*=(Caspase or GZMB) and not (BclxL or MCL1) 52 | IAP*=NFKB and not BID 53 | BclxL*=(NFKB or STAT3) and not (BID or GZMB or DISC) 54 | MCL1*=(IL2RB and STAT3 and NFKB and PI3K) and not DISC 55 | Apoptosis*=Caspase 56 | GPCR*=S1P 57 | SMAD*=GPCR 58 | SPHK1*=PDGFR 59 | S1P*=SPHK1 and not Ceramide 60 | PDGF*=PDGF 61 | IL15*=IL15 62 | Stimuli*=Stimuli 63 | Stimuli2*=Stimuli2 64 | CD45*=CD45 65 | TAX*=TAX -------------------------------------------------------------------------------- /cana/datasets/marques-pita_rocha.txt: -------------------------------------------------------------------------------- 1 | # total number of nodes 2 | .v 7 3 | 4 | # labels of nodes and names of corresponding components 5 | .l 1 One 6 | .l 2 Two 7 | .l 3 Three 8 | .l 4 Four 9 | .l 5 Five 10 | .l 6 Six 11 | .l 7 Seven 12 | 13 | # 1 = One 14 | .n 1 0 15 | 1 16 | 17 | # 2 = Two 18 | .n 2 0 19 | 1 20 | 21 | # 3 = Three 22 | .n 3 0 23 | 1 24 | 25 | # 4 = Four 26 | .n 4 0 27 | 1 28 | 29 | # 5 = Five 30 | .n 5 0 31 | 1 32 | 33 | # 6 = Six 34 | .n 6 0 35 | 1 36 | 37 | # 7 = Seven 38 | .n 7 6 1 2 3 4 5 6 39 | 000000 0 40 | 000001 0 41 | 000010 0 42 | 000011 0 43 | 000100 0 44 | 000101 0 45 | 000110 0 46 | 000111 0 47 | 001000 0 48 | 001001 1 49 | 001010 1 50 | 001011 1 51 | 001100 1 52 | 001101 1 53 | 001110 1 54 | 001111 1 55 | 010000 0 56 | 010001 0 57 | 010010 0 58 | 010011 0 59 | 010100 0 60 | 010101 0 61 | 010110 0 62 | 010111 0 63 | 011000 0 64 | 011001 0 65 | 011010 0 66 | 011011 0 67 | 011100 0 68 | 011101 0 69 | 011110 0 70 | 011111 0 71 | 100000 0 72 | 100001 0 73 | 100010 0 74 | 100011 0 75 | 100100 0 76 | 100101 0 77 | 100110 0 78 | 100111 0 79 | 101000 1 80 | 101001 1 81 | 101010 1 82 | 101011 1 83 | 101100 1 84 | 101101 1 85 | 101110 1 86 | 101111 0 87 | 110000 0 88 | 110001 0 89 | 110010 0 90 | 110011 0 91 | 110100 0 92 | 110101 0 93 | 110110 0 94 | 110111 0 95 | 111000 0 96 | 111001 0 97 | 111010 0 98 | 111011 0 99 | 111100 0 100 | 111101 0 101 | 111110 0 102 | 111111 0 103 | 104 | .e end of file -------------------------------------------------------------------------------- /cana/datasets/thaliana.txt: -------------------------------------------------------------------------------- 1 | # Boolean network model of the control of flower morphogenesis in Arabidobis thaliana 2 | # "From Genes to Flower Patterns and Evolution: Dynamic Models of Gene Regulatory Networks" 3 | # A. Chaos, M. Aldana, C. Espinosa-Soto, B. G. P. de Leon, A. G. Arroyo, E. R. Alvarez-Buylla, 4 | # Journal of Plant Growth Regulation, vol. 25, n. 4, 2006, pp. 278-289 5 | # The functions associated to nodes are minimized 6 | 7 | #total number of nodes 8 | .v 15 9 | 10 | # labels of nodes and name of corresponding genes 11 | # 1 = AP3 12 | # 2 = UFO 13 | # 3 = FUL 14 | # 4 = FT 15 | # 5 = AP1 16 | # 6 = EMF1 17 | # 7 = LFY 18 | # 8 = AP2 19 | # 9 = WUS 20 | # 10 = AG 21 | # 11 = LUG 22 | # 12 = CLF 23 | # 13 = TFL1 24 | # 14 = PI 25 | # 15 = SEP 26 | 27 | .l 1 AP3 28 | .l 2 UFO 29 | .l 3 FUL 30 | .l 4 FT 31 | .l 5 AP1 32 | .l 6 EMF1 33 | .l 7 LFY 34 | .l 8 AP2 35 | .l 9 WUS 36 | .l 10 AG 37 | .l 11 LUG 38 | .l 12 CLF 39 | .l 13 TFL1 40 | .l 14 PI 41 | .l 15 SEP 42 | 43 | 44 | # As a result of simulation, we get the following 10 single-point attractors: 45 | # 101100110111011 46 | # 110110110011011 47 | # 100110110011011 48 | # 111100110111011 49 | # 010001000011100 50 | # 010001001011100 51 | # 001100110111011 52 | # 000110110011001 53 | # 000001000011100 54 | # 000001001011100 55 | 56 | # 1 = AP3 57 | .n 1 7 1 2 5 7 10 14 15 58 | 1-1--11 1 59 | 1---111 1 60 | -1-1--- 1 61 | 62 | # 2 = UFO 63 | .n 2 1 2 64 | 1 1 65 | 66 | # 3 = FUL 67 | .n 3 2 5 13 68 | 00 1 69 | 70 | # 4 = FT 71 | .n 4 1 6 72 | 0 1 73 | 74 | # 5 = AP1 75 | .n 5 4 4 7 10 13 76 | --00 1 77 | 1-0- 1 78 | -10- 1 79 | 80 | # 6 = EMF1 81 | .n 6 1 7 82 | 0 1 83 | 84 | # 7 = LFY 85 | .n 7 4 3 5 6 13 86 | ---0 1 87 | --0- 1 88 | 89 | # 8 = AP2 90 | .n 8 1 13 91 | 0 1 92 | 93 | # 9 = WUS 94 | .n 9 3 9 10 15 95 | 1-0 1 96 | 10- 1 97 | 98 | # 10 = AG 99 | .n 10 9 5 7 8 9 10 11 12 13 15 100 | --0----0- 1 101 | -1--1---1 1 102 | -1----0-- 1 103 | -1---0--- 1 104 | 01------- 1 105 | -1-1----- 1 106 | -10------ 1 107 | 108 | # 11 = LUG 109 | .n 11 0 110 | 1 111 | 112 | # 12 = CLF 113 | .n 12 0 114 | 1 115 | 116 | # 13 = TFL1 117 | .n 13 4 5 6 7 8 118 | 010- 1 119 | 120 | # 14 = PI 121 | .n 14 6 1 5 7 10 14 15 122 | 11--11 1 123 | 1--111 1 124 | --11-- 1 125 | 1-1--- 1 126 | 127 | # 15 = SEP 128 | .n 15 1 7 129 | 1 1 130 | 131 | .e end of file 132 | 133 | -------------------------------------------------------------------------------- /cana/datasets/yeast_cell_cycle.txt: -------------------------------------------------------------------------------- 1 | .v 12 2 | 3 | .l 1 CellSize 4 | .l 2 Cln3 5 | .l 3 SBF 6 | .l 4 MBF 7 | .l 5 Cln1,2 8 | .l 6 Sic1 9 | .l 7 Clb5,6 10 | .l 8 Cdh1 11 | .l 9 Clb1,2 12 | .l 10 Mcm1/SFF 13 | .l 11 Cdc20/14 14 | .l 12 Swi5 15 | 16 | # 1 = Cell 17 | .n 1 0 18 | 19 | # 2 = Cln3 20 | .n 2 1 1 21 | 0 0 22 | 1 1 23 | 24 | # 3 = SBF 25 | .n 3 3 2 3 9 26 | 000 0 27 | 001 0 28 | 010 1 29 | 011 0 30 | 100 1 31 | 101 0 32 | 110 1 33 | 111 1 34 | 35 | # 4 = MBF 36 | .n 4 3 2 4 9 37 | 000 0 38 | 001 0 39 | 010 1 40 | 011 0 41 | 100 1 42 | 101 0 43 | 110 1 44 | 111 1 45 | 46 | # 5 = Cln1,2 47 | .n 5 1 3 48 | 0 0 49 | 1 1 50 | 51 | # 6 = Sic1 52 | .n 6 6 5 6 7 9 11 12 53 | 000000 0 54 | 000001 1 55 | 000010 1 56 | 000011 1 57 | 000100 0 58 | 000101 0 59 | 000110 0 60 | 000111 1 61 | 001000 0 62 | 001001 0 63 | 001010 0 64 | 001011 1 65 | 001100 0 66 | 001101 0 67 | 001110 0 68 | 001111 0 69 | 010000 1 70 | 010001 1 71 | 010010 1 72 | 010011 1 73 | 010100 0 74 | 010101 1 75 | 010110 1 76 | 010111 1 77 | 011000 0 78 | 011001 1 79 | 011010 1 80 | 011011 1 81 | 011100 0 82 | 011101 0 83 | 011110 0 84 | 011111 1 85 | 100000 0 86 | 100001 0 87 | 100010 0 88 | 100011 1 89 | 100100 0 90 | 100101 0 91 | 100110 0 92 | 100111 0 93 | 101000 0 94 | 101001 0 95 | 101010 0 96 | 101011 0 97 | 101100 0 98 | 101101 0 99 | 101110 0 100 | 101111 0 101 | 110000 0 102 | 110001 1 103 | 110010 1 104 | 110011 1 105 | 110100 0 106 | 110101 0 107 | 110110 0 108 | 110111 1 109 | 111000 0 110 | 111001 0 111 | 111010 0 112 | 111011 1 113 | 111100 0 114 | 111101 0 115 | 111110 0 116 | 111111 0 117 | 118 | # 7 = Cln5,6 119 | .n 7 4 4 6 7 11 120 | 0000 0 121 | 0001 0 122 | 0010 1 123 | 0011 0 124 | 0100 0 125 | 0101 0 126 | 0110 0 127 | 0111 0 128 | 1000 1 129 | 1001 0 130 | 1010 1 131 | 1011 1 132 | 1100 0 133 | 1101 0 134 | 1110 1 135 | 1111 0 136 | 137 | # 8 = Cdh1 138 | .n 8 5 5 7 8 9 11 139 | 00000 0 140 | 00001 1 141 | 00010 0 142 | 00011 0 143 | 00100 1 144 | 00101 1 145 | 00110 0 146 | 00111 1 147 | 01000 0 148 | 01001 0 149 | 01010 0 150 | 01011 0 151 | 01100 0 152 | 01101 1 153 | 01110 0 154 | 01111 0 155 | 10000 0 156 | 10001 0 157 | 10010 0 158 | 10011 0 159 | 10100 0 160 | 10101 1 161 | 10110 0 162 | 10111 0 163 | 11000 0 164 | 11001 0 165 | 11010 0 166 | 11011 0 167 | 11100 0 168 | 11101 0 169 | 11110 0 170 | 11111 0 171 | 172 | # 9 = Clb1,2 173 | .n 9 6 6 7 8 9 10 11 174 | 000000 0 175 | 000001 0 176 | 000010 1 177 | 000011 0 178 | 000100 1 179 | 000101 0 180 | 000110 1 181 | 000111 1 182 | 001000 0 183 | 001001 0 184 | 001010 0 185 | 001011 0 186 | 001100 0 187 | 001101 0 188 | 001110 1 189 | 001111 0 190 | 010000 1 191 | 010001 0 192 | 010010 1 193 | 010011 1 194 | 010100 1 195 | 010101 1 196 | 010110 1 197 | 010111 1 198 | 011000 0 199 | 011001 0 200 | 011010 1 201 | 011011 0 202 | 011100 1 203 | 011101 0 204 | 011110 1 205 | 011111 1 206 | 100000 0 207 | 100001 0 208 | 100010 0 209 | 100011 0 210 | 100100 0 211 | 100101 0 212 | 100110 1 213 | 100111 0 214 | 101000 0 215 | 101001 0 216 | 101010 0 217 | 101011 0 218 | 101100 0 219 | 101101 0 220 | 101110 0 221 | 101111 0 222 | 110000 0 223 | 110001 0 224 | 110010 1 225 | 110011 0 226 | 110100 1 227 | 110101 0 228 | 110110 1 229 | 110111 1 230 | 111000 0 231 | 111001 0 232 | 111010 0 233 | 111011 0 234 | 111100 0 235 | 111101 0 236 | 111110 1 237 | 111111 0 238 | 239 | # 10 = Mcm1/SFF 240 | .n 10 2 7 9 241 | 00 0 242 | 01 1 243 | 10 1 244 | 11 1 245 | 246 | # 11 = Cdc20&Cdc14 247 | .n 11 2 9 10 248 | 00 0 249 | 01 1 250 | 10 1 251 | 11 1 252 | 253 | # 12 = Swi5 254 | .n 12 4 9 10 11 12 255 | 0000 0 256 | 0001 0 257 | 0010 1 258 | 0011 1 259 | 0100 1 260 | 0101 1 261 | 0110 1 262 | 0111 1 263 | 1000 0 264 | 1001 0 265 | 1010 0 266 | 1011 0 267 | 1100 0 268 | 1101 0 269 | 1110 1 270 | 1111 1 271 | 272 | .e End of File -------------------------------------------------------------------------------- /cana/drawing/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/cana/drawing/__init__.py -------------------------------------------------------------------------------- /cana/drawing/canalizing_map.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Drawing the Canalizing Map (CM) 4 | ================================ 5 | 6 | Methods to draw the Canalizing Map. 7 | 8 | """ 9 | # Copyright (C) 2021 by 10 | # Rion Brattig Correia 11 | # Alex Gates 12 | # All rights reserved. 13 | # MIT license. 14 | import warnings 15 | 16 | try: 17 | import graphviz 18 | except ImportError as error: 19 | warnings.warn( 20 | "'Graphviz' could not be loaded, you won't be able to plot graphs. Try installing it first. {error:s}".format( 21 | error=error 22 | ) 23 | ) 24 | 25 | 26 | def draw_canalizing_map_graphviz( 27 | DG=None, 28 | on_node_fillcolor="black", 29 | on_node_fontcolor="white", 30 | off_node_fillcolor="white", 31 | off_node_fontcolor="black", 32 | input_node_bordercolor="gray", 33 | output_node_bordercolor="red", 34 | controlled_node_bordercolor="green", 35 | constant_node_bordercolor="pink", 36 | literal_edge_color="#208120", 37 | output_edge_color="#812020", 38 | fusing_edge_color="#a5a5cc", 39 | fused_edge_color="#202081", 40 | simplified_edge_color="#cca37a", 41 | fusing_edge_arrowhead="none", 42 | fused_edge_arrowhead="dot", 43 | literal_edge_arrowhead="dot", 44 | out_edge_arrowhead="normal", 45 | simplified_edge_arrowhead="normal", 46 | *args, 47 | **kwargs 48 | ): 49 | """Draws the Canalizing Map (CM) using the GraphViz plotting engine. 50 | 51 | Args: 52 | DG (networkx.DiGraph) : The node Canalizing Map (CM). 53 | 54 | Returns: 55 | (graphviz) : The network in graphviz dot format. 56 | """ 57 | G = graphviz.Digraph(engine="neato") 58 | G.graph_attr.update(overlap="false") 59 | G.node_attr.update( 60 | fontname="helvetica", 61 | shape="circle", 62 | fontcolor="black", 63 | fontsize="12", 64 | width=".4", 65 | fixedsize="true", 66 | style="filled", 67 | color="gray", 68 | penwidth="3", 69 | ) 70 | G.edge_attr.update(arrowhead="dot", color="gray", arrowsize="1") 71 | 72 | # Nodes 73 | for n, d in DG.nodes(data=True): 74 | if "type" not in d: 75 | raise AttributeError( 76 | "Node type could not be found. Must be either 'variable', 'threshold' or 'fusion'." 77 | ) 78 | 79 | # Variable Nodes 80 | if d["type"] == "variable": 81 | if "mode" in d: 82 | # Border Color. Dependents if 'input', 'output', 'controlled' or 'constant' 83 | if d["mode"] == "input": 84 | mode_bordercolor = input_node_bordercolor 85 | elif d["mode"] == "output": 86 | mode_bordercolor = output_node_bordercolor 87 | elif d["mode"] == "constant": 88 | mode_bordercolor = constant_node_bordercolor 89 | elif d["mode"] == "controled": 90 | mode_bordercolor = controlled_node_bordercolor 91 | else: 92 | mode_bordercolor = output_node_bordercolor 93 | 94 | if d["value"] == 0: 95 | label = d.get("label", d.get("label-tmp", "None")) 96 | G.node( 97 | name=n, 98 | label=label, 99 | fontcolor=off_node_fontcolor, 100 | fillcolor=off_node_fillcolor, 101 | color=mode_bordercolor, 102 | ) 103 | elif d["value"] == 1: 104 | label = d.get("label", d.get("label-tmp", "None")) 105 | G.node( 106 | name=n, 107 | label=label, 108 | fontcolor=on_node_fontcolor, 109 | fillcolor=on_node_fillcolor, 110 | color=mode_bordercolor, 111 | ) 112 | 113 | # Threshold Nodes 114 | elif d["type"] == "threshold": 115 | G.node( 116 | name=n, 117 | label=d["label"], 118 | shape="diamond", 119 | style="filled,solid", 120 | fillcolor="#dae8f4", 121 | fontcolor="black", 122 | color="#b5d1e9", 123 | width=".4", 124 | height=".4", 125 | ) 126 | 127 | elif d["type"] == "fusion": 128 | G.node(name=n, label="", shape="none", width="0", height="0", margin="0") 129 | 130 | # Edges 131 | for s, t, d in DG.edges(data=True): 132 | color = literal_edge_color 133 | arrowhead = out_edge_arrowhead 134 | 135 | if "type" in d: 136 | if d["type"] == "out": 137 | arrowhead = out_edge_arrowhead 138 | color = output_edge_color 139 | 140 | elif d["type"] == "literal": 141 | arrowhead = literal_edge_arrowhead 142 | color = literal_edge_color 143 | 144 | elif d["type"] == "fusing": 145 | arrowhead = fusing_edge_arrowhead 146 | color = fusing_edge_color 147 | 148 | elif d["type"] == "fused": 149 | arrowhead = fused_edge_arrowhead 150 | color = fused_edge_color 151 | 152 | elif d["type"] == "simplified": 153 | if d["mode"] == "selfloop": 154 | arrowhead = simplified_edge_arrowhead 155 | color = simplified_edge_color 156 | elif d["mode"] == "direct": 157 | arrowhead = simplified_edge_arrowhead 158 | color = simplified_edge_color 159 | 160 | else: 161 | raise AttributeError( 162 | "Node type could not be found. Must be either 'out', 'literal', 'fusing', 'fused' or 'simplified'. Got {:s}.".format( 163 | d["type"] 164 | ) 165 | ) 166 | G.edge(s, t, arrowhead=arrowhead, color=color) 167 | 168 | return G 169 | -------------------------------------------------------------------------------- /docs/source/appendix/index.rst: -------------------------------------------------------------------------------- 1 | Appendix 2 | ============== 3 | 4 | External information and supplemental code in other languages. 5 | 6 | R 7 | ---- 8 | 9 | Here we also distribute the R code used to compute boolean network ensembles and criticality measures :cite:`GatesManickaMarquesRocha:2016`. 10 | 11 | :download:`download ` -------------------------------------------------------------------------------- /docs/source/appendix/smanicka_r_code.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/docs/source/appendix/smanicka_r_code.zip -------------------------------------------------------------------------------- /docs/source/bibliography.rst: -------------------------------------------------------------------------------- 1 | Bibliography 2 | ============ 3 | 4 | .. bibliography:: refs.bib 5 | :style: alpha -------------------------------------------------------------------------------- /docs/source/conf.py: -------------------------------------------------------------------------------- 1 | # Configuration file for the Sphinx documentation builder. 2 | # 3 | # This file only contains a selection of the most common options. For a full 4 | # list see the documentation: 5 | # https://www.sphinx-doc.org/en/master/usage/configuration.html 6 | 7 | # -- Path setup -------------------------------------------------------------- 8 | 9 | # If extensions (or modules to document with autodoc) are in another directory, 10 | # add these directories to sys.path here. If the directory is relative to the 11 | # documentation root, use os.path.abspath to make it absolute, like shown here. 12 | # 13 | # import os 14 | # import sys 15 | # sys.path.insert(0, os.path.abspath('.')) 16 | from cana import __package__, __copyright__, __author__, __version__, __release__ 17 | 18 | # -- Project information ----------------------------------------------------- 19 | 20 | project = __package__.upper() 21 | copyright = __copyright__ 22 | author = __author__ 23 | 24 | # The full version, including alpha/beta/rc tags 25 | release = __release__ 26 | version = __version__ 27 | 28 | 29 | # -- General configuration --------------------------------------------------- 30 | 31 | # Add any Sphinx extension module names here, as strings. They can be 32 | # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom 33 | # ones. 34 | extensions = [ 35 | "sphinx.ext.intersphinx", 36 | "sphinx.ext.autodoc", 37 | "sphinx.ext.doctest", 38 | "sphinx.ext.mathjax", 39 | "sphinx.ext.viewcode", 40 | "sphinx.ext.todo", 41 | "sphinx.ext.ifconfig", 42 | "sphinx.ext.coverage", 43 | "sphinx.ext.napoleon", 44 | "sphinx.ext.autosummary", 45 | "sphinxcontrib.bibtex", 46 | ] 47 | 48 | # Add any paths that contain templates here, relative to this directory. 49 | templates_path = ['_templates'] 50 | 51 | # List of patterns, relative to source directory, that match files and 52 | # directories to ignore when looking for source files. 53 | # This pattern also affects html_static_path and html_extra_path. 54 | exclude_patterns = [] 55 | 56 | 57 | # -- Options for HTML output ------------------------------------------------- 58 | 59 | # The theme to use for HTML and HTML Help pages. See the documentation for 60 | # a list of builtin themes. 61 | # 62 | html_theme = 'sphinx_rtd_theme' 63 | 64 | # Add any paths that contain custom static files (such as style sheets) here, 65 | # relative to this directory. They are copied after the builtin static files, 66 | # so a file named "default.css" will overwrite the builtin "default.css". 67 | html_static_path = ['_static'] 68 | 69 | # Google Analytcis 70 | googleanalytics_id = 'UA-71404006-4' 71 | 72 | # bibtex configuration 73 | bibtex_bibfiles = ['refs.bib'] 74 | bibtex_default_style = 'plain' 75 | bibtex_reference_style = 'label' 76 | 77 | # Napoleon settings 78 | napoleon_google_docstring = True 79 | napoleon_numpy_docstring = True 80 | 81 | -------------------------------------------------------------------------------- /docs/source/index.rst: -------------------------------------------------------------------------------- 1 | 2 | CANAlization: Control & Redundancy in Boolean Networks 3 | ====================================================== 4 | 5 | This package implements a series of methods used to study control, canalization and redundancy in Boolean Networks. 6 | 7 | If you are using this package, please consider citing the following papers: 8 | 9 | :cite:`Gates:2021` "A.J. Gates, R.B. Correia, X. Wang, & L.M. Rocha [2021]. "`The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling`__". *Proceedings of the National Academy of Sciences (PNAS)*, **118** (12). doi: 10.1073/pnas.2022598118" 10 | 11 | __ https://doi.org/10.1073/pnas.2022598118 12 | 13 | :cite:`CANA:2018` "R.B. Correia, A. Gates, X. Wang and L.M. Rocha [2018]. "`CANA: A python package for quantifying control and canalization in Boolean Networks`__." *Frontiers in Physiology*, **9**: 1046. doi: 10.3389/fphys.2018.01046." 14 | 15 | __ https://www.informatics.indiana.edu/rocha/publications/FSB18.php 16 | 17 | :cite:`Gates:2016` "A. Gates and L.M. Rocha. [2016] "`Control of complex networks requires both structure and dynamics`__." *Scientific Reports* **6**, 24456. doi: 10.1038/srep24456." 18 | 19 | __ http://www.informatics.indiana.edu/rocha/publications/NSR16.php 20 | 21 | :cite:`Gates:2014` "A. Gates and L.M. Rocha [2014]. "`Structure and dynamics affect the controllability of complex systems`__: a Preliminary Study". *Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems*: 429-430, MIT Press." 22 | 23 | __ http://www.informatics.indiana.edu/rocha/publications/alife14a.html 24 | 25 | :cite:`Marques-Pita:2013` "M. Marques-Pita and L.M. Rocha [2013]. "`Canalization and control in automata networks: body segmentation in Drosophila Melanogaster`__". *PLoS ONE*, **8** (3): e55946. doi:10.1371/journal.pone.0055946." 26 | 27 | __ http://www.informatics.indiana.edu/rocha/publications/plos2012.html 28 | 29 | 30 | Documentation: 31 | -------------- 32 | 33 | **Tutorials**: For examples of utilization pleasee see tutorials in `github.com/rionbr/CANA`__. 34 | 35 | __ https://github.com/rionbr/CANA/tree/master/tutorials 36 | 37 | .. toctree:: 38 | :maxdepth: 3 39 | :caption: Table of Contents: 40 | 41 | reference/index 42 | appendix/index 43 | bibliography 44 | 45 | 46 | Indices and tables 47 | ================== 48 | 49 | * :ref:`genindex` 50 | * :ref:`modindex` 51 | * :ref:`search` 52 | -------------------------------------------------------------------------------- /docs/source/reference/canalization/index.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.canalization 2 | 3 | Canalization 4 | ============== 5 | 6 | .. automodule:: cana.canalization.boolean_canalization 7 | :members: -------------------------------------------------------------------------------- /docs/source/reference/control/index.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.boolean_network 2 | 3 | Control 4 | ======= 5 | 6 | These are methods and modules used to calculate control in Boolean Networks. They are divided in dynamics- and structure-based methods. 7 | 8 | Note that these methods do not need to be called directly, as :class:`cana.boolean_network.BooleanNetwork` provides the appropriate methods. 9 | 10 | .. contents:: Contents 11 | :depth: 3 12 | 13 | Dynamics based control 14 | ------------------------ 15 | 16 | The control methods used here are implemented directly on the base class :class:`.BooleanNetwork` and :class:`.BooleanNode`. That is because the Network class can ask its nodes directly to step into a specific trajectory, thus compartmentalizing the logic. 17 | 18 | Attractor Control 19 | ^^^^^^^^^^^^^^^^^ 20 | 21 | .. automethod:: cana.boolean_network.BooleanNetwork.attractor_driver_nodes 22 | :noindex: 23 | 24 | .. automethod:: cana.boolean_network.BooleanNetwork.controlled_state_transition_graph 25 | :noindex: 26 | 27 | .. automethod:: cana.boolean_network.BooleanNetwork.controlled_attractor_graph 28 | :noindex: 29 | 30 | Structure based control 31 | ----------------------- 32 | 33 | These are control methods that only take the structure of the boolean network (aka: the structure graph) into consideration when computing driver nodes. 34 | 35 | .. automodule:: cana.control.fvs 36 | :members: 37 | 38 | .. automodule:: cana.control.mds 39 | :members: 40 | 41 | .. automodule:: cana.control.sc 42 | :members: -------------------------------------------------------------------------------- /docs/source/reference/datasets/index.rst: -------------------------------------------------------------------------------- 1 | 2 | Datasets 3 | ======== 4 | 5 | Preloaded Boolean nodes and networks that can be directly instanciated. 6 | A set of more than 70 Boolean networks from the Cell Collective are also available. 7 | 8 | .. toctree:: 9 | :maxdepth: 1 10 | 11 | nodes 12 | networks -------------------------------------------------------------------------------- /docs/source/reference/datasets/networks.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.datasets 2 | 3 | 4 | .. automodule:: cana.datasets.bio 5 | :members: 6 | 7 | .. automodule:: cana.datasets.motifs 8 | :members: 9 | -------------------------------------------------------------------------------- /docs/source/reference/datasets/nodes.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.datasets 2 | 3 | 4 | .. automodule:: cana.datasets.bools 5 | :members: 6 | -------------------------------------------------------------------------------- /docs/source/reference/ensemble.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.random_boolean_network 2 | 3 | Ensemble Methods 4 | ================ 5 | 6 | .. automodule:: cana.random_boolean_network 7 | :members: -------------------------------------------------------------------------------- /docs/source/reference/index.rst: -------------------------------------------------------------------------------- 1 | API Reference 2 | ============== 3 | 4 | :Version: |version| 5 | :Release: |release| 6 | :Date: |today| 7 | 8 | 9 | .. toctree:: 10 | :caption: Table of Contents 11 | :name: mastertoc 12 | :maxdepth: 2 13 | 14 | node 15 | network 16 | canalization/index 17 | control/index 18 | datasets/index 19 | ensemble 20 | utils 21 | -------------------------------------------------------------------------------- /docs/source/reference/network.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.boolean_network 2 | 3 | Network 4 | ======== 5 | 6 | .. contents:: Contents 7 | :depth: 3 8 | 9 | .. automodule:: cana.boolean_network 10 | 11 | .. autoclass:: BooleanNetwork 12 | :members: 13 | 14 | 15 | .. automodule:: cana.bns 16 | :members: -------------------------------------------------------------------------------- /docs/source/reference/node.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana.boolean_node 2 | 3 | Node 4 | ===== 5 | 6 | .. automodule:: cana.boolean_node 7 | .. autoclass:: BooleanNode 8 | :members: -------------------------------------------------------------------------------- /docs/source/reference/utils.rst: -------------------------------------------------------------------------------- 1 | .. currentmodule:: cana 2 | 3 | Utilities 4 | ========== 5 | 6 | .. automodule:: cana.utils 7 | :members: -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [build-system] 2 | requires = [ 3 | "setuptools", 4 | # "Cython", 5 | "wheel", 6 | ] 7 | build-backend = "setuptools.build_meta" 8 | [tool.pytest.ini_options] 9 | pythonpath = [".", "tests/", "tests/helpers/"] 10 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | astroid==2.15.4 2 | click==8.1.3 3 | contourpy==1.0.7 4 | cycler==0.11.0 5 | dill==0.3.6 6 | flake8==6.0.0 7 | fonttools==4.43.0 8 | iniconfig==2.0.0 9 | isort==5.12.0 10 | kiwisolver==1.4.4 11 | lazy-object-proxy==1.9.0 12 | matplotlib==3.9.0 13 | mccabe==0.7.0 14 | mypy==1.2.0 15 | mypy-extensions==1.0.0 16 | networkx==3.3 17 | numpy==1.26.4 18 | packaging==23.1 19 | pandas==2.2.2 20 | pathspec==0.11.1 21 | Pillow==10.3.0 22 | platformdirs==3.5.0 23 | pluggy==1.0.0 24 | pycodestyle==2.10.0 25 | pyflakes==3.0.1 26 | pylint==2.17.3 27 | pyparsing==3.0.9 28 | pytest==7.3.1 29 | python-dateutil==2.8.2 30 | pytz==2023.3 31 | removestar==1.3.1 32 | schematodes==1.0.0 33 | scipy==1.13.1 34 | six==1.16.0 35 | tomlkit==0.11.8 36 | typing_extensions==4.5.0 37 | tzdata==2023.3 38 | wrapt==1.15.0 39 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import Extension, find_packages, setup 2 | 3 | # from Cython.Build import cythonize 4 | 5 | 6 | def readme(): 7 | with open("README.md") as f: 8 | return f.read() 9 | 10 | 11 | # cythonize awesomeness 12 | # ext_modules = ["cana/cutils.pyx", "cana/canalization/cboolean_canalization.pyx"] 13 | extensions = [ 14 | Extension("cana.cutils", ["cana/cutils.c"]), 15 | Extension( 16 | "cana.canalization.cboolean_canalization", 17 | ["cana/canalization/cboolean_canalization.c"], 18 | ), 19 | ] 20 | 21 | __package__ = "cana" 22 | __description__ = "This package implements a series of methods used to study control, canalization and redundancy in Boolean networks." 23 | __version__ = "1.0.0" 24 | 25 | setup( 26 | name=__package__, 27 | version=__version__, 28 | description=__description__, 29 | long_description=__description__, 30 | long_description_content_type="text/plain", 31 | classifiers=[ 32 | "Development Status :: 4 - Beta", 33 | "License :: OSI Approved :: MIT License", 34 | "Programming Language :: Python :: 3", 35 | "Intended Audience :: Science/Research", 36 | "Topic :: Scientific/Engineering :: Information Analysis", 37 | ], 38 | keywords="boolean networks canalization redundancy dynamical systems computational biology", 39 | url="http://github.com/rionbr/CANA", 40 | author="Alex Gates & Rion Brattig Correia", 41 | author_email="rionbr@gmail.com", 42 | license="MIT", 43 | packages=find_packages(), 44 | package_data={ 45 | "datasets": [ 46 | "cana.datasets/*.txt", 47 | "cana.datasets/bns/*.cnet", 48 | "cana.datasets/cell_collective/*.txt", 49 | ], 50 | }, 51 | install_requires=[ 52 | "numpy", 53 | "scipy", 54 | "networkx", 55 | "pandas", 56 | "matplotlib", 57 | "schematodes>=1.0.0", 58 | # 'Cython' 59 | ], 60 | include_package_data=True, 61 | zip_safe=False, 62 | # ext_modules=cythonize(ext_modules, include_path=[''], compiler_directives={'language_level': '3'}) # cython awesomeness 63 | ext_modules=extensions, 64 | ) 65 | -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CASCI-lab/CANA/05a9794b5129a74a422db10153e2fdde9e78a922/tests/__init__.py -------------------------------------------------------------------------------- /tests/helpers/helper.py: -------------------------------------------------------------------------------- 1 | # helper functions for testing apparatus 2 | import math 3 | import random 4 | from itertools import permutations, product 5 | 6 | from cana.boolean_node import BooleanNode 7 | from cana.datasets.bio import load_all_cell_collective_models 8 | 9 | 10 | def randNode(k): 11 | """Create a BooleaNode with random function at a given $k$""" 12 | func = [random.randint(0, 1) for i in range(2**k)] 13 | return BooleanNode(k=k, inputs=list(range(k)), outputs=func) 14 | 15 | 16 | def reorderTwoSymbolOutput(tss): 17 | """Convert a list of two-symbol schemata to a set of two-symbol schemata with unique orderings for equality testing. 18 | 19 | arguments: 20 | tss -- two-symbol schemata list, [ (string, [[]], [[]]) ] 21 | """ 22 | tssNew = set() 23 | for ts in tss: 24 | symGroups = ts[1] 25 | schemata = list(ts[0]) 26 | for sg in symGroups: 27 | sgNew = sorted(sg) 28 | symsInSg = sorted([(i, schemata[i]) for i in sgNew], key=lambda x: x[1]) 29 | for i, sym in zip(sgNew, [i[1] for i in symsInSg]): 30 | schemata[i] = sym 31 | tssNew.add( 32 | ("".join(schemata), frozenset(frozenset(i) for i in ts[1]), frozenset()) 33 | ) # WARNING: ignoring same-symbol symmetry for now 34 | return tssNew 35 | 36 | 37 | def expandTs(ts): 38 | """Expand a two-symbol schemata to the set of all schema (with don't cares) it encodes""" 39 | # expand ts 40 | tss = [i[0] for i in ts] 41 | perms = [i[1] for i in ts] 42 | obsSet = set() 43 | # for each schema and its symmetries 44 | for t, g in zip(tss, perms): 45 | if type(t) == str: 46 | t = list(t) 47 | # for each subset of indices that can be permuted 48 | x = [] 49 | for idxs in g: 50 | # produce all permutations of those indices 51 | x.append([(idxs, i) for i in permutations([t[j] for j in idxs], len(idxs))]) 52 | # get cross-product of groups 53 | cxs = list(product(*x)) 54 | # can apply each sequence in each item of cross product 55 | for seq in cxs: 56 | tPerm = t.copy() 57 | for p in seq: 58 | for i, j in zip(p[0], p[1]): 59 | tPerm[i] = j 60 | obsSet.add("".join(tPerm)) 61 | return obsSet 62 | 63 | 64 | def enumerateImplicants(func): 65 | """Enumerate the input conditions and their outputs of the given function""" 66 | implicants = {"0": set(), "1": set()} 67 | k = int(math.log(len(func)) / math.log(2)) 68 | for i, output in enumerate(func, start=0): 69 | cond = f"{bin(i)[2:]:0>{k}}" 70 | implicants[output].add(cond) 71 | return implicants 72 | 73 | 74 | # each element of pi is a string 75 | def expandPi(pi): 76 | """Expand a schemata with don't cares into the set of all schema it encodes""" 77 | out = set() 78 | for s in pi: 79 | # count number of 2s 80 | n = sum(1 for i in s if int(i) == 2) 81 | idxs = [i for i in range(len(s)) if s[i] == "2"] 82 | # get all permutations of 0 and 1 of that length 83 | # for perm in permutations("01", n): 84 | for perm in product(*["01"] * n): 85 | # print(perm) 86 | slist = list(s) 87 | # produce substitution of each 88 | for k, i in enumerate(idxs): 89 | slist[i] = perm[k] 90 | out.add("".join(slist)) 91 | return out 92 | 93 | 94 | def compare(pi, ts): 95 | """test if two functions represented by schemata are the same. 96 | Args: 97 | pi: the one-symbol schemata of function 1 98 | ts: the two-symbol schemata of function 2 99 | Returns: 100 | 3-tuple (bool, set, set) 101 | """ 102 | x = expandPi(expandTs(ts)) 103 | y = expandPi(pi) 104 | return x == y, x - y, y - x 105 | 106 | 107 | def getPis(outputs): 108 | """Compute prime implicants from a string function representation""" 109 | k = int(math.log(len(outputs)) / math.log(2)) 110 | node = BooleanNode(k=k, inputs=range(k), outputs=list(outputs)) 111 | node._check_compute_canalization_variables(prime_implicants="i dont matter") 112 | pi = node._prime_implicants 113 | return { 114 | 0: set(i.replace("#", "2") for i in pi["0"]), 115 | 1: set(i.replace("#", "2") for i in pi["1"]), 116 | } 117 | 118 | 119 | def getCCnodes(): 120 | networks = load_all_cell_collective_models() 121 | nodes = [] 122 | for network in networks: 123 | for node in network.nodes: 124 | if ( 125 | node.k < 8 and "1" in node.outputs and "0" in node.outputs 126 | ): # select non-constant with k<=7 127 | nodes.append(node) 128 | # fs = ["".join(n.outputs) for n in nodes] 129 | return nodes 130 | -------------------------------------------------------------------------------- /tests/test_boolean_network.py: -------------------------------------------------------------------------------- 1 | from cana.boolean_network import BooleanNetwork 2 | import networkx as nx 3 | from cana.datasets.bio import THALIANA 4 | 5 | def test_EG_weight_THALIANA(): 6 | """Test that effective graph in-degree edge weights are computed correctly.""" 7 | network = THALIANA() 8 | network.effective_graph() 9 | 10 | true = [] 11 | for i, node in enumerate(network.nodes): 12 | # get sum from nx object 13 | edgews = {edge: network._eg.edges[edge]["weight"] for edge in network._eg.edges if edge[1]==i} 14 | true.append(sum(edgews.values())) 15 | assert network.effective_indegrees() == sorted(true, reverse=True) 16 | -------------------------------------------------------------------------------- /tests/test_effectiveness_measures.py: -------------------------------------------------------------------------------- 1 | from cana.boolean_node import BooleanNode 2 | import math 3 | 4 | measures = [ 5 | "kr", 6 | "kr_norm", 7 | "ke", 8 | "ke_norm", 9 | "a", 10 | "s", 11 | "s_norm" 12 | # "kc", 13 | # "kc_norm" 14 | ] 15 | 16 | def doTest(func, ans): 17 | k = int(math.log(len(func)) / math.log(2)) 18 | node = BooleanNode(k=k, inputs=range(k), outputs=list(func)) 19 | 20 | rets = {} 21 | for m in measures: 22 | if m == "kr": 23 | rets[m] = node.input_redundancy(norm=False) 24 | elif m == "kr_norm": 25 | rets[m] = node.input_redundancy(norm=True) 26 | elif m == "ke": 27 | rets[m] = node.effective_connectivity(norm=False) 28 | elif m == "ke_norm": 29 | rets[m] = node.effective_connectivity(norm=True) 30 | elif m == "a": 31 | rets[m] = node.activities() 32 | elif m == "s": 33 | rets[m] = node.sensitivity(norm=False) 34 | elif m == "s_norm": 35 | rets[m] = node.sensitivity(norm=True) 36 | # elif m == "kc": 37 | # rets[m] = node.effective_connectivity(norm=False) - node.sensitivity(norm=False) 38 | # elif m == "kc_norm": 39 | # rets[m] = node.effective_connectivity(norm=True) - node.sensitivity(norm=True) 40 | 41 | for m in measures: 42 | assert rets[m] == ans[m], m 43 | 44 | def test_AND(): 45 | f = "0001" 46 | ans = { 47 | "kr": 3/4, 48 | "kr_norm": 3/4/2, 49 | "ke": 5/4, 50 | "ke_norm": 5/4/2, 51 | "a": [0.5, 0.5], 52 | "s": 1, 53 | "s_norm": 1/2 54 | } 55 | doTest(f, ans) -------------------------------------------------------------------------------- /tests/test_two_symbol_symmetry.py: -------------------------------------------------------------------------------- 1 | import math 2 | 3 | import helpers.helper as helper 4 | 5 | from cana.boolean_node import BooleanNode 6 | from cana.canalization.boolean_canalization import * # WARNING: some functions here differ from the file below! 7 | from cana.canalization.cboolean_canalization import * 8 | from cana.cutils import outputs_to_binstates_of_given_type 9 | 10 | # WARNING: ignoring detection of same-symbol symmetry for now. Complicating issues. 11 | 12 | 13 | def getTss(outputs): 14 | """Compute unique representation of two-symbol schemata from Boolean output table. 15 | Assume that prime-implicant calculation is correct. 16 | 17 | arguments: 18 | outputs -- string representing the lookup table of the function, going from input 0...0 to 1...1 19 | """ 20 | k = int(math.log(len(outputs)) / math.log(2)) 21 | node = BooleanNode(k=k, inputs=range(k), outputs=list(outputs)) 22 | node._check_compute_canalization_variables(two_symbols="i dont matter") 23 | ts0, ts1 = node._two_symbols 24 | 25 | return {0: ts0, 1: ts1} 26 | 27 | 28 | def test_cc(): 29 | """Test two-symbol symmetry correctness for all Cell Collective nodes. 30 | Note: currently only does so for non-constant nodes with k<=7. 31 | """ 32 | nodes = helper.getCCnodes() 33 | fails = [] 34 | log = [] 35 | for node in nodes: 36 | f = node.outputs 37 | ts = getTss(f) 38 | pi = helper.getPis(f) 39 | for y in [0, 1]: 40 | x = helper.compare(pi[y], ts[y]) 41 | if not x[0]: # False if not same sets 42 | fails.append(x) 43 | log.append( 44 | ", ".join( 45 | [ 46 | node.network.name, 47 | node.name, 48 | "".join(str(i) for i in node.outputs), 49 | str(y), 50 | str(node.k), 51 | str(pi), 52 | str(ts), 53 | ] 54 | ) 55 | ) 56 | # print(len(fails), fails) 57 | # print([i for i in fails if i[2] != set()]) 58 | with open("bulk_test_log.csv", "w") as fd: 59 | columns = ["network", "node", "function", "PIs", "k", "pi", "ts"] 60 | fd.write(", ".join(columns)) 61 | fd.write("\n") 62 | fd.write("\n".join(log)) 63 | assert len(fails) == 0, f"{len(fails)} failures" 64 | 65 | 66 | def doTSStest(func, true_ts0, true_ts1): 67 | """Test whether the two-symbol calculation of a given function matches the manually-computed answer.""" 68 | true_ts0 = helper.reorderTwoSymbolOutput(true_ts0) 69 | true_ts1 = helper.reorderTwoSymbolOutput(true_ts1) 70 | tsss = getTss(func) 71 | 72 | assert helper.reorderTwoSymbolOutput(tsss[0]) == true_ts0, tsss[0] 73 | assert helper.reorderTwoSymbolOutput(tsss[1]) == true_ts1, tsss[1] 74 | 75 | 76 | def test_two_symbol_AND(): 77 | f = "0001" 78 | true_ts0 = [("20", [[0, 1]], [])] 79 | true_ts1 = [("11", [], [[0, 1]])] 80 | doTSStest(f, true_ts0, true_ts1) 81 | 82 | 83 | def test_two_symbol_OR(): 84 | f = "0111" 85 | true_ts0 = [("00", [], [])] 86 | true_ts1 = [("12", [[0, 1]], [])] 87 | doTSStest(f, true_ts0, true_ts1) 88 | 89 | 90 | def test_two_symbol_AB_C(): 91 | f = "01010111" 92 | t0 = [("020", [[0, 1]], [])] 93 | t1 = [("112", [], []), ("221", [], [])] 94 | doTSStest(f, t0, t1) 95 | 96 | 97 | def test_two_symbol_ABC(): 98 | f = "00000001" 99 | t0 = [("022", [[0, 1, 2]], [])] 100 | t1 = [("111", [], [])] 101 | doTSStest(f, t0, t1) 102 | 103 | 104 | def test_two_symbol_AB_CD_lv1(): 105 | f = "0001000100011111" 106 | t0 = [ 107 | ("0202", [[0, 1], [2, 3]], []), 108 | ] 109 | t1 = [("1122", [], []), ("2211", [], [])] 110 | doTSStest(f, t0, t1) 111 | 112 | 113 | # NOTE: this is a test for when it can detect two groups at once in this case 114 | # def test_two_symbol_AB_CD_lv2(): 115 | # f = "0001000100011111" 116 | # t0 = [ 117 | # ("0202", [[0,1],[2,3]], []), # WARNING should this one have same-symbol permutations? 118 | # ] 119 | # t1 = [ 120 | # ("1122", [], []), 121 | # ("2211", [], []) 122 | # ] 123 | # doTSStest(f, t0, t1) 124 | 125 | 126 | def test_two_symbol_AP3(): 127 | f = "00000000000000000000000000000000000000001111111100000000111111110000000100000001000100010001000100000001111111110001000111111111" 128 | t0 = [("2002022", [[1, 3]], []), ("2022220", [[0, 5, 6], [1, 3]], [])] 129 | t1 = [("2121222", [], []), ("1222111", [[2, 4]], [])] 130 | doTSStest(f, t0, t1) 131 | 132 | 133 | def test_symbol_LFY(): 134 | f = "1110111011101110" 135 | t0 = [("2211", [], [])] 136 | t1 = [("2202", [[2, 3]], [])] 137 | doTSStest(f, t0, t1) 138 | 139 | 140 | def test_two_symbol_Thaliana_AG(): 141 | f = "11001100110011001100110011001100110011001100110011001100110011000000000000000000000000000000000000000000000000000000000000000000111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111100110011001100110011001100110011001100110011001100110011001100000000000000000000000000000000000000000000000000000000000000000011111111111111111111111111111111111111111111111111111111111111111111111111110000111111111111010111111111111111111111111111111111" 142 | t0 = [("121001122", [[4, 8]], []), ("201222222", [[2, 7]], [])] 143 | t1 = [ 144 | ("220222202", [], []), 145 | ("212212221", [], []), 146 | ("212122222", [], []), 147 | ("012222222", [[0, 2, 5, 6]], []), 148 | ] 149 | doTSStest(f, t0, t1) 150 | 151 | 152 | def test_two_symbol_BuddingYeast_Cdh1(): 153 | f = "01001101000001000000010000000000" 154 | t0 = [ 155 | ("22020", [], []), 156 | ("21212", [[0, 1, 3]], []), 157 | ("21220", [[0, 1, 3], [2, 4]], []), 158 | ] 159 | t1 = [("00201", [[2, 4]], []), ("00121", [[0, 1, 3]], [])] 160 | doTSStest(f, t0, t1) 161 | 162 | 163 | def test_two_symbol_Lymphoid_IL7r(): 164 | f = "0000000000000000010101010100010000001111000011000101111101001100" 165 | t0 = [ 166 | ("221212", [], []), 167 | ("002222", [[0, 3], [1, 5]], []), 168 | ] 169 | t1 = [("210221", [[2, 4]], []), ("120122", [[2, 4]], [])] 170 | doTSStest(f, t0, t1) 171 | 172 | 173 | if __name__ == "__main__": 174 | test_two_symbol_Lymphoid_IL7r() 175 | --------------------------------------------------------------------------------