├── Books └── temp └── README.md /Books/temp: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Deep-Learning-in-Bioinformatics-Papers-Reading-Roadmap 2 | >If you are a newcomer to apply the the Deep Learning in bioinformatics area, the first question you may have is "What is the profile of deep learning in bioinformatics at present?" 3 | 4 | >Here is a reading roadmap of papers applying Deep Learning in bioinformatics! 5 | 6 | Those papers are mainly published in _Nature_, _Nature Methods_, _Nature protocols_, _NAR_, _Briefings in Bioinformatics_, _Bioinformatics_, _Drug Discovery Today_, _Genome Research_, _Genome Biology_, _PLoS computational biology_, _JCIM_, _JPR_, _Distill Pub_, _CACM_, _JACM_, _JMLR_, and _NIPS_. 7 | 8 | The recently added journals are _AC_, _Nature Chemistry_, _Nature Reviews Chemistry_, and _Nature structural & molecular biology_. 9 | 10 | I would continue adding papers to this roadmap. 11 | 12 |
13 | 14 | --------------------------------------- 15 | ## -2. LCMS-based proteomics 16 | **[0]** Zhifei Zhang. "**pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.**" AC. (November 10, 2017). 17 | 18 | **[0]** Naohiro Kobayashi. "**Noise peak filtering in multi-dimensional NMR spectra using convolutional neural networks.**" Bioinformatics. (09 July 2018). 19 | 20 | **[1]** Ming Li. "**De novo peptide sequencing by deep learning.**" PNAS. (July 18, 2017). 21 | 22 | ## -1. GCMS-based metabolomics 23 | **[0]** SKARYSZ, A. ... et al, . "**Convolutional neural networks for automated targeted analysis of raw gas chromatography–mass spectrometry data.**" IJCNN 2018. (2018). 24 | 25 | ## 0. Drug discovery 26 | **[0]** Hongmei Lu. "**Deep-Learning-Based Drug–Target Interaction Prediction.**" JPR. (March 6, 2017) 27 | 28 | **[1]** Jianyang Zeng. "**NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions.**" Bioinformatics. (02 July 2018) 29 | 30 | **[0]** Pierre Baldi. "**Deep Learning in Biomedical Data Science.**" Annual Review of Biomedical Data Science. (2018). 31 | 32 | ## 1. Biomacromolecular structure prediction 33 | 34 | **[0]** Yaoqi Zhou. "**Accurate Prediction of Protein Contact Maps by Coupling Residual Two-Dimensional Bidirectional Long Short-Term Memory with Convolutional Neural Networks.**" Bioinformatics. (19 June 2018). 35 | 36 | **[1]** Jinbo Xu. "**ComplexContact: a web server for inter-protein contact prediction using deep learning.**" NAR. (22 May 2018). 37 | 38 | **[2]** Jinbo Xu. "**Protein threading using residue co-variation and deep learning.**" Bioinformatics. (1 July 2018). 39 | 40 | 41 | ## 2. Cell 42 | 43 | **[0]** Jianzhu Ma. "**Using deep learning to model the hierarchical structure and function of a cell.**" Nature Methods. (2018-04). **(ps)** :star::star::star::star::star: 44 | 45 | ## 3. Transcription factor-DNA binding 46 | 47 | **[0]** Abdullah M Khamis. "**DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants.**" NAR. (02 April 2018). **(ps)** :star::star::star::star::star: 48 | 49 | 50 | ## 4. lncRNAs related 51 | 52 | **[0]** Sungroh Yoon. "**lncRNAnet: Long Non-coding RNA Identification using Deep Learning.**" Bioinformatics. (29 May 2018). 53 | 54 | **[1]** Huaiqiu Zhu. "**LncADeep: An ab initio lncRNA identification and functional annotation tool based on deep learning.**" Bioinformatics. (29 May 2018). 55 | 56 | [^_^]: 57 | **[0]** authors. "**template.**" journal. (date). 58 | 59 | 60 | ## 5. Gene expression related 61 | 62 | **[0]** Tianwei Yu. "**A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data.**" Bioinformatics. (29 May 2018). 63 | 64 | **[1]** Wesley De Neve. "**SpliceRover: Interpretable Convolutional Neural: Networks for Improved Splice Site Prediction.**" Bioinformatics. (21 June 2018). 65 | 66 | **[2]** David A Hendrix. "**A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.**" NAR. (09 July 2018) 67 | 68 | 69 | ### ^Before September 2017 (only a few widely influential papers were selected) 70 | 71 | **[0]** LuZhang, JianjunTan, DanHan, HaoZhu. "**From machine learning to deep learning: progress in machine intelligence for rational drug discovery.**" Drug Discovery Today. 72 | 73 | **[1]** Dapeng Xiong, Jianyang Zeng, and Haipeng Gong. "**A deep learning framework for improving long-range residue–residue contact prediction using a hierarchical strategy.**" Bioinformatics. 74 | 75 | **[2]** Yeeleng S. Vang, Xiaohui Xie. "**HLA class I binding prediction via convolutional neural networks.**" Bioinformatics. 76 | 77 | **[3]** Baoji He, S. M. Mortuza, Yanting Wang, Hong-Bin Shen, Yang Zhang."**NeBcon: protein contact map prediction using neural network training coupled with naïve Bayes classifiers.**" Bioinformatics. 78 | 79 | **[4]** Nansu Zong, Hyeoneui Kim, Victoria Ngo, Olivier Harismendy. "**Deep mining heterogeneous networks of biomedical linked data to predict novel drug–target associations.**" Bioinformatics. 80 | 81 | **[5]** José Juan Almagro Armenteros et al. "**DeepLoc: Prediction of protein subcellular localization using deep learning.**" Bioinformatics. 82 | 83 | **[6]** Bite Yang et al. "**BiRen: predicting enhancers with a deep-learning-based model using the DNA sequence alone.**" Bioinformatics. 84 | 85 | **[7]** William J. Godinez et al. "**A multi-scale convolutional neural network for phenotyping high-content cellular images.**" Bioinformatics. 86 | 87 | **[8]** Xiuquan Du, Yanping Zhang et al. "**DeepPPI: Boosting Prediction of Protein–Protein Interactions with Deep Neural Networks.**" JCIM. 88 | 89 | **[9]** Moritz Hess et al. "**Partitioned learning of deep Boltzmann machines for SNP data.**" Bioinformatics. 90 | 91 | **[10]** Travers Ching et al. "**Opportunities and obstacles for deep learning in biology and medicine.**" bioRxiv. 92 | 93 | **[11]** A Esteva et al. "**Dermatologist-level classification of skin cancer with deep neural networks.**" Nature. (FEB 2 2017). 94 | 95 | **[12]** Seonwoo Min et al. "**Deep learning in bioinformatics.**" Briefings in bioinformatics. (16 June 2016). 96 | 97 |
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