├── .gitignore ├── RDF_output └── semrep_1.xml ├── RDFizer.py ├── README.md ├── SemRep_RDFizer.sh ├── images ├── PubAnnotation_json.jpg ├── SemRep+PubAnnotation.jpg ├── SemRepRDF_Open.gliffy ├── SemRepRDF_Open.jpg ├── SempRep_PA_triples.gliffy └── SempRep_PA_triples.jpg └── requirements.txt /.gitignore: -------------------------------------------------------------------------------- 1 | # Distribution / packaging 2 | .Python 3 | build/ 4 | develop-eggs/ 5 | dist/ 6 | downloads/ 7 | eggs/ 8 | .eggs/ 9 | lib/ 10 | lib64/ 11 | parts/ 12 | sdist/ 13 | var/ 14 | wheels/ 15 | *.egg-info/ 16 | .installed.cfg 17 | *.egg 18 | 19 | # Installer logs 20 | pip-log.txt 21 | pip-delete-this-directory.txt 22 | 23 | # Unit test / coverage reports 24 | htmlcov/ 25 | .tox/ 26 | .coverage 27 | .coverage.* 28 | .cache 29 | nosetests.xml 30 | coverage.xml 31 | *.cover 32 | .hypothesis/ 33 | 34 | # Jupyter Notebook 35 | .ipynb_checkpoints 36 | 37 | # Environments 38 | .env 39 | .idea/ 40 | 41 | # specific scripts 42 | RDFizer.ipynb 43 | README.md 44 | 45 | #directories 46 | images/drafts/ 47 | 48 | #data 49 | SemRepRDF_PMIDS.tsv -------------------------------------------------------------------------------- /RDF_output/semrep_1.xml: -------------------------------------------------------------------------------- 1 | 2 | 11 | 12 | 13 | 165 14 | ti 15 | 228 16 | 17 | 18 | 19 | 20 | Formate assay in body fluids: application in methanol poisoning. 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 178 35 | 173 36 | 37 | 38 | 39 | 1975 40 | 1 41 | 42 | 43 | 44 | 165 45 | 172 46 | 47 | 48 | 49 | 50 | 178 51 | 52 | 165 53 | 54 | 55 | 56 | 209 57 | 207 58 | 59 | 60 | 61 | 1.7 62 | 63 | SemRep 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | formate 72 | 73 | Methyl alcohol poisoning 74 | 75 | 76 | 77 | Assay 78 | 79 | 80 | 81 | 82 | 83 | 84 | USES 85 | 86 | DIAGNOSES 87 | 88 | 89 | 90 | 210 91 | 228 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | -------------------------------------------------------------------------------- /RDFizer.py: -------------------------------------------------------------------------------- 1 | ########################################################################################## 2 | # RDFizer.py 3 | # Purpose: convert SemRep predications into RDF triples 4 | # version 1.0.0 5 | # date: 12.19.2017 6 | # Python 2.7.13 7 | # ################################### 8 | # Licensing: The SemRep (Database Version 3.0_A; SemRep Version 1.7; Date 12/31/2016) is the original source of the 9 | # predications. Neither the United States Government, the U.S. Department of Health and Human Services, the National 10 | # Institutes of Health, the National Library of Medicine, the Lister Hill National Center for Biomedical Communications, 11 | # nor any of their agencies, contractors, subcontractors, or employees make any warranties, expressed or implied, with 12 | # respect to the SKR resources, and furthermore, they assume no liability for any party's use, or the results of such 13 | # use, of any part of these tools. For the SemRepRDF-Open version, minor modifications to the original SemRep 14 | # predications include the mapping of UMLS CUIs to open resource concept identifiers. 15 | ########################################################################################## 16 | 17 | 18 | ##NEEDS: 19 | #1. Dockers for triples and docker that can download SemMedDB instance 20 | #2. autmoatic build 21 | #3. add github topics to repo/create a wikipage for it 22 | #4. write testing 23 | #5. think through combining with PubAnnotation - and or the way that we will map the UMLS concepts to other 24 | # terminologies 25 | #6. add wording to top of output file to be in compliance with terms and use agreement. 26 | 27 | # install needed libraries 28 | import argparse 29 | import base64 30 | from functools import partial 31 | import hashlib 32 | import multiprocessing 33 | from mysql.connector import Error, errorcode 34 | import MySQLdb 35 | import os 36 | import sys 37 | from rdflib import Namespace 38 | from rdflib.namespace import RDF, DCTERMS, RDFS 39 | from rdflib import Graph 40 | from rdflib import URIRef, Literal 41 | 42 | 43 | 44 | 45 | 46 | def DBConnect(host, username, password, db): 47 | """ 48 | Function takes several strings and an integer that contain information on how to connect to a MySQL database 49 | containing the SemMedDB database instance. The function returns a string representing the cursor object necessary 50 | for querying the database as well as a string that stores the database connection (needed to close the connection 51 | to the database after querying is complete). 52 | 53 | :param host: string representing the database host name 54 | :param username: string representing the database username 55 | :param password: string representing the database password 56 | :param db: string representing the database name 57 | 58 | :return: strings representing the cursor object necessary for querying the database and the database object 59 | """ 60 | 61 | try: 62 | cnx = MySQLdb.connect(host=host, 63 | user=username, 64 | passwd=password, 65 | db=db) 66 | # verify that connection to database is valid 67 | except Error as err: 68 | if err.errno == errorcode.ER_ACCESS_DENIED_ERROR: 69 | print("Something is wrong with your user name or password") 70 | elif err.errno == errorcode.ER_BAD_DB_ERROR: 71 | print("Database does not exist") 72 | else: 73 | print(err) 74 | else: 75 | return cnx 76 | 77 | 78 | 79 | def QueryRunner(db_info, query): 80 | """ 81 | Function takes a list storing information needed to access MySQL database and a string storing an SQL query as 82 | input. The query is then processed against the database via the cursor. Prior to returning results, the function 83 | verifies that query returned data, otherwise an exception is raised. The function returns a list of lists where 84 | each list contains one row of output. 85 | 86 | :param db_info (list): list of information needed to connect to a database 87 | :param query (str): string storing an SQL query 88 | 89 | :return: list of lists where each list contains one row of output 90 | """ 91 | 92 | # execute query against a MySQL DB 93 | db_cnx = DBConnect(db_info[0], db_info[1], db_info[2], db_info[3]) 94 | cursor = db_cnx.cursor() 95 | cursor.execute(query) 96 | 97 | # verify that query returned results 98 | if int(cursor.rowcount) > 0: 99 | return cursor.fetchall() 100 | else: 101 | raise Exception("Query returned no results") 102 | 103 | 104 | 105 | def SentenceSpan(db_info, sentence_id): 106 | """Function takes a list storing information needed to access MySQL database and a string storing an identifier. The 107 | function uses this information to run a query against the database. The query uses the string identifier to retrieve 108 | all start and end indices for the given identifier. Prior to returning results, the function verifies that the 109 | returned start and stop indices for the sentence make sense (i.e., that the stop index is equal to or larger 110 | than the start index, otherwise an exception is raised. The function returns a list of start and stop indexes. 111 | 112 | :param db_info (list): list of information needed to connect to a database 113 | :param sentence_id (str): sentence identifier 114 | 115 | :return: a list of start and stop indices for the input sentence identifier 116 | """ 117 | 118 | sent_span = QueryRunner(db_info, 119 | ("select p.SENTENCE_ID, " 120 | " MIN(LEAST(pa.PREDICATE_START_INDEX, pa.SUBJECT_START_INDEX, pa.OBJECT_START_INDEX))," 121 | " MAX(GREATEST(pa.PREDICATE_END_INDEX, pa.SUBJECT_END_INDEX, pa.OBJECT_END_INDEX))" 122 | " from SemMedDB.PREDICATION p " 123 | " inner join SemMedDB.PREDICATION_AUX pa on pa.PREDICATION_ID = p.PREDICATION_ID" 124 | " where p.SENTENCE_ID = " + "'" + str(sentence_id) + "'" + 125 | " GROUP BY p.SENTENCE_ID")) 126 | 127 | # verify that query returned results 128 | if int(sent_span[0][2]) >= int(sent_span[0][1]): 129 | return str(sent_span[0][1]), str(sent_span[0][2]) 130 | else: 131 | raise Exception("Sentence start and end indices are incorrect") 132 | 133 | 134 | 135 | def TripleMaker(pmid, db_info): 136 | """ 137 | 138 | :param pmid: 139 | :param db_info: 140 | :return: 141 | """ 142 | 143 | ## GET DATA FOR TRIPLES ## 144 | # run query to get results needed for generating triples 145 | res = [map(str, x) for x in QueryRunner(db_info, 146 | ("select *" 147 | " from SemMedDB.PREDICATION p" 148 | " inner join SemMedDB.SENTENCE s on s.SENTENCE_ID = p.SENTENCE_ID" \ 149 | " inner join " 150 | "SemMedDB.CITATIONS c on c.PMID = p.PMID" \ 151 | " inner join SemMedDB.PREDICATION_AUX pa on pa.PREDICATION_ID = " 152 | "p.PREDICATION_ID" \ 153 | " where p.PMID = " + "'" + str(pmid) + "'" 154 | " order by p.PREDICATION_ID"))] 155 | 156 | # get database version information 157 | vers = [map(str, x) for x in QueryRunner(db_info, ("select * from SemMedDB.METAINFO"))] 158 | version = base64.b64encode(hashlib.sha1("semrep" + str(vers[0][1])).digest()) 159 | 160 | ##CREATE TRIPLES 161 | 162 | # add namespaces 163 | nlm = Namespace("https://skr3.nlm.nih.gov/") 164 | oa = Namespace("http://www.w3.org/ns/oa#") 165 | oa_ext = Namespace("http://www.weneedaurl.now/") 166 | obo = Namespace("http://purl.obolibrary.org/obo/") 167 | prov = Namespace("http://www.w3.org/ns/prov#") 168 | sep = Namespace("http://purl.obolibrary.org/obo/sep/") 169 | swo = Namespace("http://purl.obolibrary.org/obo/swo/") 170 | tao = Namespace("http://pubannotation.org/ontology/tao.owl#") 171 | umls = Namespace("http://uts-ws.nlm.nih.gov/rest/content/current/CUI/") 172 | 173 | # add identifiers 174 | prj = "http://pubannotation.org/projects/semrep/" 175 | doc = "http://pubannotation.org/docs/sourcedb/PMC/sourceid/" + str(pmid) + "/divs/0" 176 | sent = "http://pubannotation.org/projects/sentences/PMC-" + str(pmid) + "-0-sentence_" 177 | span = "http://pubannotation.org/docs/sourcedb/PMC/sourceid/" + str(pmid) + "/divs/0/spans/" 178 | concept = "http://pubannotation.org/projects/sentences/PMC-" + str(pmid) + "-0-T_" 179 | 180 | # create graph 181 | g = Graph() 182 | annot_graph = base64.b64encode(hashlib.sha1(str(pmid)).digest()) 183 | 184 | # document provenance 185 | g.add((URIRef(str(prj) + str(annot_graph)), URIRef(str(oa) + 'has_source'), URIRef(str(doc)))) 186 | g.add((URIRef(str(doc)), DCTERMS.published, Literal(str(res[0][21])))) 187 | g.add((URIRef(str(doc)), RDF.type, URIRef(str(obo) + "IAO_0000310"))) 188 | g.add((URIRef(str(doc)), DCTERMS.identifier, Literal(str(pmid)))) 189 | 190 | # annotation description triples 191 | g.add((URIRef(str(prj) + str(annot_graph)), URIRef(str(prov) + 'atTime'), URIRef(str(vers[0][2])))) 192 | g.add((URIRef(str(prj) + str(annot_graph)), URIRef(str(prov) + 'wasGeneratedBy'), URIRef(str(nlm) + str(version)))) 193 | g.add((URIRef(str(prj) + str(annot_graph)), RDF.type, URIRef(str(prov) + 'Activity'))) 194 | g.add((URIRef(str(prj) + str(annot_graph)), RDF.type, URIRef(str(oa_ext) + 'OA_Concept_Annotation'))) 195 | g.add((URIRef(str(nlm) + str(version)), URIRef(str(sep) + 'SEP_00065'), Literal(str(vers[0][1])))) 196 | g.add((URIRef(str(nlm) + str(version)), RDF.type, URIRef(str(swo) + 'SWO_0000001'))) 197 | g.add((URIRef(str(nlm) + str(version)), RDFS.label, Literal("SemRep"))) 198 | 199 | 200 | # loop over predications and add annotations to graph 201 | for annot in res: 202 | 203 | # get sentence span information 204 | sent_span = SentenceSpan(db_info, annot[1]) 205 | 206 | # resource description 207 | sents = str(sent) + str(annot[1]) 208 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'belongs_to'), URIRef(str(doc)))) 209 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'begins_at'), Literal(str(sent_span[0])))) 210 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'ends_at'), Literal(str(sent_span[1])))) 211 | g.add((URIRef(str(sents)), DCTERMS.source, Literal(str(annot[14])))) 212 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'has_text'), Literal(str(annot[16])))) 213 | g.add((URIRef(str(sents)), RDF.type, URIRef(str(tao) + 'Text_span'))) 214 | 215 | # subject 216 | span1 = str(span) + str(annot[27]) + "-" + str(annot[28]) 217 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'contains'), URIRef(str(span1)))) 218 | g.add((URIRef(str(span1)), URIRef(str(tao) + 'begins_at'), Literal(str(annot[27])))) 219 | g.add((URIRef(str(span1)), URIRef(str(tao) + 'ends_at'), Literal(str(annot[28])))) 220 | 221 | if '|' in annot[4]: 222 | for con in annot[4].split('|'): 223 | concept1 = str(concept) + str(con) 224 | g.add((URIRef(str(span1)), URIRef(str(tao) + 'denotes'), URIRef(str(concept1)))) 225 | g.add((URIRef(str(concept1)), RDF.type, URIRef(str(tao) + 'Concept_entity'))) 226 | g.add((URIRef(str(concept1)), RDF.type, URIRef(str(RDF) + 'Subject'))) 227 | g.add((URIRef(str(RDF) + 'Subject'), DCTERMS.identifier, URIRef(str(umls) + str(annot[4])))) 228 | g.add((URIRef(str(RDF) + 'Subject'), RDFS.label, Literal(str(annot[5])))) 229 | else: 230 | concept1 = str(concept) + str(annot[4]) 231 | g.add((URIRef(str(span1)), URIRef(str(tao) + 'denotes'), URIRef(str(concept1)))) 232 | g.add((URIRef(str(concept1)), RDF.type, URIRef(str(tao) + 'Concept_entity'))) 233 | g.add((URIRef(str(concept1)), RDF.type, URIRef(str(RDF) + 'Subject'))) 234 | g.add((URIRef(str(RDF) + 'Subject'), DCTERMS.identifier, URIRef(str(umls) + str(annot[4])))) 235 | g.add((URIRef(str(RDF) + 'Subject'), RDFS.label, Literal(str(annot[5])))) 236 | 237 | # predicate 238 | span2 = str(span) + str(annot[31]) + "-" + str(annot[32]) 239 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'contains'), URIRef(str(span2)))) 240 | g.add((URIRef(str(span2)), URIRef(str(tao) + 'begins_at'), Literal(str(annot[31])))) 241 | g.add((URIRef(str(span2)), URIRef(str(tao) + 'ends_at'), Literal(str(annot[32])))) 242 | 243 | if '|' in annot[3]: 244 | for con in annot[3].split('|'): 245 | concept2 = str(concept) + str(con) 246 | g.add((URIRef(str(span2)), URIRef(str(tao) + 'denotes'), URIRef(str(concept1)))) 247 | g.add((URIRef(str(concept2)), RDF.type, URIRef(str(tao) + 'Concept_entity'))) 248 | g.add((URIRef(str(concept2)), RDF.type, URIRef(str(RDF) + 'Predicate'))) 249 | g.add((URIRef(str(RDF) + 'Predicate'), DCTERMS.identifier, URIRef(str(umls) + str(annot[3])))) 250 | g.add((URIRef(str(RDF) + 'Predicate'), RDFS.label, Literal(str(annot[3])))) 251 | else: 252 | concept2 = str(concept) + str(annot[3]) 253 | g.add((URIRef(str(span2)), URIRef(str(tao) + 'denotes'), URIRef(str(concept1)))) 254 | g.add((URIRef(str(concept2)), RDF.type, URIRef(str(tao) + 'Concept_entity'))) 255 | g.add((URIRef(str(concept2)), RDF.type, URIRef(str(RDF) + 'Predicate'))) 256 | g.add((URIRef(str(RDF) + 'Predicate'), DCTERMS.identifier, URIRef(str(umls) + str(annot[3])))) 257 | g.add((URIRef(str(RDF) + 'Predicate'), RDFS.label, Literal(str(annot[3])))) 258 | 259 | # object 260 | span3 = str(span) + str(annot[36]) + "-" + str(annot[37]) 261 | g.add((URIRef(str(sents)), URIRef(str(tao) + 'contains'), URIRef(str(span3)))) 262 | g.add((URIRef(str(span3)), URIRef(str(tao) + 'begins_at'), Literal(str(annot[36])))) 263 | g.add((URIRef(str(span3)), URIRef(str(tao) + 'ends_at'), Literal(str(annot[37])))) 264 | 265 | if '|' in annot[8]: 266 | for con in annot[8].split('|'): 267 | concept3 = str(concept) + str(con) 268 | g.add((URIRef(str(span3)), URIRef(str(tao) + 'denotes'), URIRef(str(concept3)))) 269 | g.add((URIRef(str(concept3)), RDF.type, URIRef(str(tao) + 'Concept_entity'))) 270 | g.add((URIRef(str(concept3)), RDF.type, URIRef(str(RDF) + 'Object'))) 271 | g.add((URIRef(str(RDF) + 'Object'), DCTERMS.identifier, URIRef(str(umls) + str(annot[8])))) 272 | g.add((URIRef(str(RDF) + 'Object'), RDFS.label, Literal(str(annot[9])))) 273 | else: 274 | concept3 = str(concept) + str(annot[8]) 275 | g.add((URIRef(str(span3)), URIRef(str(tao) + 'denotes'), URIRef(str(concept3)))) 276 | g.add((URIRef(str(concept3)), RDF.type, URIRef(str(tao) + 'Concept_entity'))) 277 | g.add((URIRef(str(concept3)), RDF.type, URIRef(str(RDF) + 'Object'))) 278 | g.add((URIRef(str(RDF) + 'Object'), DCTERMS.identifier, URIRef(str(umls) + str(annot[8])))) 279 | g.add((URIRef(str(RDF) + 'Object'), RDFS.label, Literal(str(annot[9])))) 280 | 281 | # graph-level triples 282 | g.add((URIRef(str(span1)), URIRef(str(tao) + 'follows'), URIRef(str(span2)))) 283 | g.add((URIRef(str(span2)), URIRef(str(tao) + 'follows'), URIRef(str(span3)))) 284 | 285 | # serialize annotation graph for pmid 286 | out = "RDF_output/semrep_" + str(pmid) 287 | g.serialize(destination=str(out) + ".xml", format='xml') 288 | 289 | 290 | 291 | 292 | def main(): 293 | parser = argparse.ArgumentParser(description='SemRepRDF: This program is designed to ') 294 | parser.add_argument('-h', '--host', help='MySQL host information', required=True) 295 | parser.add_argument('-u', '--user', help='MySQL username information', required=True) 296 | parser.add_argument('-p', '--passwd', help='MySQL root information', required=True) 297 | parser.add_argument('-d', '--db', help='MySQL password information', required=True) 298 | args = parser.parse_args() 299 | 300 | # set default encoding to utf8 301 | reload(sys) 302 | sys.setdefaultencoding('utf8') # needed to parse article titles 303 | 304 | # connect to database 305 | # db_info = [args.host, args.user, args.passwd, args.db] 306 | db_info = ['', 'root', 'YRUS9bjb', 'SemMedDB'] 307 | 308 | # retrieve all pubmed ids to facilitate parallel processing 309 | pmids = [str(id[0]) for id in QueryRunner(db_info, ("select PMID from SemMedDB.CITATIONS"))] 310 | 311 | # configure multiprocessing settings 312 | pool = multiprocessing.Pool() # set up pool 313 | func = partial(TripleMaker, db_info) 314 | triples = pool.map(func, pmids) 315 | 316 | # close and join pool 317 | pool.close() 318 | pool.join() 319 | 320 | if __name__ == '__main__': 321 | main() 322 | 323 | 324 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # SemRepRDF 2 | This repository contains code used to transform the National Library of Medicine’s Semantic Representation (SemRep) predications into open semantically-linked annotations. Please see the Wiki for more details. 3 | 4 | 5 | ## Getting Started 6 | 7 | To obtain an RDFized version of SemRep, download the zip file or fork the project repository. Additional instructions can be found under [*Installation*](Installation). 8 | 9 | 10 | ### Installation 11 | 12 | This program was written on a system running OS X Sierra. Successful execution of this program requires Python version 2.7. 13 | 14 | * Python 2.7.13 modules 15 | * Native Modules: base64, hashlib, multiprocessing, MySQLdb, os, sys 16 | * To download needed modules run the following from the working directory of the project folder: 17 | 18 | ``` 19 | pip install -r requirements.txt 20 | ``` 21 | 22 | * Semantic MEDLINE Database 23 | * If using SemRepRDF-UMLS, you will need to obtain a free [UMLS license](https://www.nlm.nih.gov/research/umls/) 24 | * Download and configure the latest SemMedDB MySQL data dump [SemMedDB](https://skr3.nlm.nih.gov/SemMedDB/dbinfo.html) 25 | 26 | * Although not a requirement, the program has been written to run in parallel on a super computer. 27 | 28 | 29 | ## Running Program 30 | 31 | The program can be run from the command line via argparse arguments. 32 | 33 | ``` 34 | # from project directory - find help menu 35 | tiffanycallahan$ python RDFizer.py -h 36 | 37 | 38 | 39 | # to run the program 40 | tiffanycallahan$ python RDFizer.py 41 | 42 | ``` 43 | 44 | ## Versioning 45 | 46 | We use [SemVer](http://semver.org/) for versioning. 47 | 48 | ## Testing 49 | 50 | 51 | ## License 52 | Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. 53 | 54 | This repository generates two different kinds of output that are subject to two different kind of licensing (see details regarding these representations on the [Wiki](https://github.com/callahantiff/SemRepRDF/wiki/Licensing)): 55 | 1. The SemRepRDF-UMLS representation uses concepts that are part of the UMLS Metathesaurus and are thus subject to the [UMLS license agreement](https://uts.nlm.nih.gov/license.html). 56 | 2. The SemRepRDF-LOD version has been generated in such a way that all annotated concept identifiers come only from terminologies, vocabularies, and ontologies with open license agreements. Minor modifications to the original SemRep predications include the mapping of UMLS CUIs to open resource concept identifiers. 57 | 58 | #### SemRepRDF-Open Resources and Tools 59 | 60 | Table of UMLS Metathesaurus vocabularies and NLM tools used when generating SemRepRDF-LOD. For details regarding how each of these sources will be used when generating SemRepRDF-LOD, see Wiki page on [Resource Mapping](https://github.com/callahantiff/SemRepRDF/wiki/UMLS-Concept-and-Relation-Mapping). 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 210 |
SourceVersionLicenseTerms of Use
RESOUCES
Anatomical Therapeutic Chemical (ATC) 2017AB Non-Commercial Use of all or parts of the material requires reference to the WHO Collaborating Centre for Drug Statistics Methodology. Copying and distribution for commercial purposes is not allowed. Additional Information. Changing or manipulating the material is not allowed.
DrugBank 2017AB CC BY-NC 4.0 DrugBank is offered to the public as a freely available resource. Use and re-distribution of the data, in whole or in part, for commercial purposes (including internal use) requires a license. Additional Information
Gene Ontology (GO) 2017AB CC-BY 4.0 The GOC wishes the users and consumers of GO data publicly display the date(s) and/or version number(s) of the relevant GO files, data, or software version. The GO is evolving and changes regularly--this information is critical to downstream consumers and users. Additional Information
HUGO Gene Nomenclature Committee (HGNC) 2017AB It is a condition of our funding from NIH and the Wellcome Trust that the nomenclature and information we provide is freely available to all. Anyone may use the HGNC data, but we request that they reference the "HUGO Gene Nomenclature Committee at the European Bioinformatics Institute" and the website where possible. Additional Information
Human Phenotype Ontology (HPO) 2017AB The HPO vocabularies, annotation files, tools and documentation are freely available. The HPO is copyrighted to protect the integrity of the vocabularies, which means that changes to the HPO vocabularies need to be done by HPO developers. However, anyone can download the HPO and use the ontologies or other HPO files under three conditions: 106 |
    107 |
  • That the Human Phenotype Ontology Consortium is acknowledged and cited properly.
    • 108 |
  • That any HPO Consortium file(s) displayed publicly include the date(s) and/or version number(s) of the relevant HPO file(s).
    • 109 |
  • That neither the content of the HPO file(s) nor the logical relationships embedded within the HPO file(s) be altered in any way. (Content additions and modifications have to be suggested using our issue tracker).
    • 110 |
  • We suggest that you follow standard scientific citation practice if you use the HPO in publications.
    5)Services and products have to display a short acknowledgement statement, that makes clear that the service/product is using HPO.
    • 111 |
112 | Additional Information
The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) 2017AB Not specified in readme when downloaded Availible for download via ftp through the CDC. Additional Information
The International Classification of Diseases, Tenth Revision (ICD10) 2017AB WHO is able to issue internal licences to organizations wishing to incorporate WHO 126 | classifications into their internal information systems for use by employees for use for 127 | administrative purposes eg. health records management". For more information regarding guidelines for using resource, see link. Additional Information
The International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD10-PCS) 2017AB WHO is able to issue internal licences to organizations wishing to incorporate WHO 135 | classifications into their internal information systems for use by employees for use for 136 | administrative purposes eg. health records management. For more information regarding guidelines for using resource, see link. Additional Information
The Logical Observation Identifiers Names and Codes terminology (LOINC) 2017AB Licensed and Copyrighted, free to use The Terms of Use are very detailed, see link. Additional Information
NCBI Taxonomy 2017AB Databases of molecular data on the NCBI Web site include such examples as nucleotide sequences (GenBank), protein sequences, macromolecular structures, molecular variation, gene expression, and mapping data. They are designed to provide and encourage access within the scientific community to sources of current and comprehensive information. Therefore, NCBI itself places no restrictions on the use or distribution of the data contained therein. Nor do we accept data when the submitter has requested restrictions on reuse or redistribution. For more information regarding guidelines for using resource, see link. Additional Information
National Drug File - Reference Terminology 2017AB UMLS Category 0 license; but vocabulary can be downloaded from NCI without license or registration. For more information regarding guidelines for using resource, see link. Additional Information
Foundational Model of Anatomy (FMA) 2017AB Licensed through the University of Washington, which states "The Foundational Model of Anatomy ontology (FMA) is OPEN SOURCE and available for general use". For more information regarding guidelines for using resource, see link. Additional Information
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211 | 212 | ## Acknowledgments 213 | 214 | * Project completed as part of the 4th annual Biomedical Linked Annotation Hackathon ([BLAH](http://blah4.linkedannotation.org)) held in Kashiwa, Japan. 215 | 216 | * README was generated from a modified markdown template originally created by **Billie Thompson [PurpleBooth](https://github.com/PurpleBooth)**. 217 | 218 | -------------------------------------------------------------------------------- /SemRep_RDFizer.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | if ! 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