{"id":"https://openalex.org/W2004320937","doi":"https://doi.org/10.1145/2500863.2500870","title":"Drug-target interaction prediction for drug repurposing with probabilistic similarity logic","display_name":"Drug-target interaction prediction for drug repurposing with probabilistic similarity logic","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2004320937","doi":"https://doi.org/10.1145/2500863.2500870","mag":"2004320937"},"language":"en","primary_location":{"id":"doi:10.1145/2500863.2500870","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2500863.2500870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Workshop on Data Mining in Bioinformatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077611411","display_name":"Shobeir Fakhraei","orcid":"https://orcid.org/0000-0001-8532-6023"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shobeir Fakhraei","raw_affiliation_strings":["University of Maryland, College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054150982","display_name":"Louiqa Raschid","orcid":"https://orcid.org/0000-0002-0630-6049"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Louiqa Raschid","raw_affiliation_strings":["University of Maryland, College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086169451","display_name":"Lise Getoor","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lise Getoor","raw_affiliation_strings":["University of Maryland, College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":2.6074,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89322018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"10","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10375","display_name":"Pharmacogenetics and Drug Metabolism","score":0.9606999754905701,"subfield":{"id":"https://openalex.org/subfields/3004","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drug-repositioning","display_name":"Drug repositioning","score":0.7269362211227417},{"id":"https://openalex.org/keywords/drugbank","display_name":"DrugBank","score":0.692446231842041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6831070184707642},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5887067317962646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5795038342475891},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5465332269668579},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.534437894821167},{"id":"https://openalex.org/keywords/drug-drug-interaction","display_name":"Drug-drug interaction","score":0.45921823382377625},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44928833842277527},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42814186215400696},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.31421393156051636}],"concepts":[{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.7269362211227417},{"id":"https://openalex.org/C155261790","wikidata":"https://www.wikidata.org/wiki/Q1122544","display_name":"DrugBank","level":3,"score":0.692446231842041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6831070184707642},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5887067317962646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5795038342475891},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5465332269668579},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.534437894821167},{"id":"https://openalex.org/C2910466267","wikidata":"https://www.wikidata.org/wiki/Q718753","display_name":"Drug-drug interaction","level":3,"score":0.45921823382377625},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44928833842277527},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42814186215400696},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.31421393156051636},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2500863.2500870","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2500863.2500870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Workshop on Data Mining in Bioinformatics","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.352.9102","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.9102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://linqs.cs.umd.edu/basilic/web/Publications/2013/fakhraei:biokdd13/FakhraeiBioKDD13.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6744841964","display_name":null,"funder_award_id":"IIS0746930, CCF0937094, IIS1218488","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"},{"id":"https://openalex.org/G8503809664","display_name":null,"funder_award_id":"IIS0746930, CCF0937094, IIS1218488","funder_id":"https://openalex.org/F4320337387","funder_display_name":"Division of Computing and Communication Foundations"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337387","display_name":"Division of Computing and Communication Foundations","ror":"https://ror.org/01mng8331"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W66443818","https://openalex.org/W92973652","https://openalex.org/W188755909","https://openalex.org/W1490768968","https://openalex.org/W1521843029","https://openalex.org/W1522260031","https://openalex.org/W1544009106","https://openalex.org/W1659833910","https://openalex.org/W1979104937","https://openalex.org/W1984084871","https://openalex.org/W2009313526","https://openalex.org/W2017102965","https://openalex.org/W2021579368","https://openalex.org/W2029980980","https://openalex.org/W2040022355","https://openalex.org/W2063149926","https://openalex.org/W2079745490","https://openalex.org/W2098889731","https://openalex.org/W2111076982","https://openalex.org/W2113072832","https://openalex.org/W2121604817","https://openalex.org/W2138512826","https://openalex.org/W2139736926","https://openalex.org/W2140538501","https://openalex.org/W2142572836","https://openalex.org/W2150698190","https://openalex.org/W2151084213","https://openalex.org/W2153838454","https://openalex.org/W2153959628","https://openalex.org/W2162723805","https://openalex.org/W2597851033","https://openalex.org/W2754351509","https://openalex.org/W3003709066","https://openalex.org/W4234229624","https://openalex.org/W6603669155"],"related_works":["https://openalex.org/W4387572939","https://openalex.org/W3114988578","https://openalex.org/W4390649784","https://openalex.org/W4387767168","https://openalex.org/W4390539447","https://openalex.org/W4385514295","https://openalex.org/W2797260394","https://openalex.org/W3035455406","https://openalex.org/W3177397016","https://openalex.org/W4205482548"],"abstract_inverted_index":{"The":[0],"high":[1],"development":[2],"cost":[3],"and":[4,79,99,121,160,172],"low":[5],"success":[6],"rate":[7],"of":[8,68,75,105,108,125,149,176],"drug":[9,38],"discovery":[10],"from":[11,153],"new":[12],"compounds":[13],"highlight":[14],"the":[15,115,134,174,177],"need":[16],"for":[17,24,36,114,128,203],"methods":[18,29],"to":[19,61],"discover":[20],"alternate":[21],"therapeutic":[22],"effects":[23],"currently":[25],"approved":[26],"drugs.":[27],"Computational":[28],"can":[30,101],"be":[31],"effective":[32],"in":[33,64,87,168,199],"focusing":[34],"efforts":[35],"such":[37],"repurposing.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43,89,192],"propose":[44],"a":[45,65,73,106,147],"novel":[46],"drug-target":[47,69,150,169,179,204],"interaction":[48,129,170,180,205],"prediction":[49,59,63,140,171,181,198],"framework":[50],"based":[51,96,117],"on":[52,97,118,146],"probabilistic":[53,83],"similarity":[54,109,127],"logic":[55,85],"(PSL)":[56],"[5].":[57],"Interaction":[58],"corresponds":[60],"link":[62,94,197],"bipartite":[66],"network":[67],"interactions":[70,151],"extended":[71],"with":[72,157,184],"set":[74],"similarities":[76],"between":[77,80],"drugs":[78],"targets.":[81],"Using":[82],"first-order":[84],"rules":[86,92,116],"PSL,":[88],"show":[90,132],"how":[91],"describing":[93],"predictions":[95],"triads":[98],"tetrads":[100],"effectively":[102],"make":[103,196],"use":[104],"variety":[107],"measures.":[110],"We":[111,131,142,164],"learn":[112],"weights":[113,137],"training":[119],"data,":[120],"report":[122],"relative":[123],"importance":[124],"each":[126],"prediction.":[130,206],"that":[133,195],"learned":[135],"rule":[136],"significantly":[138],"improve":[139],"precision.":[141],"evaluate":[143],"our":[144,185],"results":[145],"dataset":[148],"obtained":[152],"Drugbank":[154],"[27]":[155],"augmented":[156],"five":[158],"drug-based":[159],"three":[161],"target-based":[162],"similarities.":[163],"integrate":[165],"domain":[166],"knowledge":[167],"match":[173],"performance":[175],"state-of-the-art":[178],"systems":[182],"[22]":[183],"model":[186],"using":[187],"simple":[188],"triad-based":[189],"rules.":[190],"Furthermore,":[191],"apply":[193],"techniques":[194],"PSL":[200],"more":[201],"efficient":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
