{"id":"https://openalex.org/W2807792492","doi":"https://doi.org/10.24963/ijcai.2018/468","title":"Interpretable Drug Target Prediction Using Deep Neural Representation","display_name":"Interpretable Drug Target Prediction Using Deep Neural Representation","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2807792492","doi":"https://doi.org/10.24963/ijcai.2018/468","mag":"2807792492"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/468","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/468","pdf_url":"https://www.ijcai.org/proceedings/2018/0468.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0468.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113838969","display_name":"Kyle Yingkai Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Yingkai Gao","raw_affiliation_strings":["IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062643837","display_name":"Achille Fokoue","orcid":"https://orcid.org/0000-0003-1137-1344"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Achille Fokoue","raw_affiliation_strings":["IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047001057","display_name":"Heng Luo","orcid":"https://orcid.org/0000-0001-5192-8878"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heng Luo","raw_affiliation_strings":["IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102744844","display_name":"Arun Iyengar","orcid":"https://orcid.org/0000-0003-4679-1920"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arun Iyengar","raw_affiliation_strings":["IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001532090","display_name":"Sanjoy Kumer Dey","orcid":"https://orcid.org/0000-0003-1236-7232"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjoy Dey","raw_affiliation_strings":["IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050360222","display_name":"Ping Zhang","orcid":"https://orcid.org/0000-0002-4601-0779"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ping Zhang","raw_affiliation_strings":["IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":250,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3371","last_page":"3377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9800999760627747,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7799631357192993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7180795669555664},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6176124215126038},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5990302562713623},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5972166061401367},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5859514474868774},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5798825621604919},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5751634836196899},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.555591344833374},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.5253937840461731},{"id":"https://openalex.org/keywords/drug-target","display_name":"Drug target","score":0.5155572891235352},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5035585761070251},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4480944275856018},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43405431509017944},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3885319232940674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07840052247047424},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07690843939781189}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7799631357192993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7180795669555664},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6176124215126038},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5990302562713623},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5972166061401367},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5859514474868774},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5798825621604919},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5751634836196899},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.555591344833374},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5253937840461731},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.5155572891235352},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5035585761070251},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4480944275856018},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43405431509017944},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3885319232940674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07840052247047424},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07690843939781189},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2018/468","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/468","pdf_url":"https://www.ijcai.org/proceedings/2018/0468.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/468","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/468","pdf_url":"https://www.ijcai.org/proceedings/2018/0468.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2807792492.pdf","grobid_xml":"https://content.openalex.org/works/W2807792492.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W2054141820","https://openalex.org/W2064675550","https://openalex.org/W2103017472","https://openalex.org/W2104950117","https://openalex.org/W2109991441","https://openalex.org/W2127589108","https://openalex.org/W2134967712","https://openalex.org/W2139516171","https://openalex.org/W2156798505","https://openalex.org/W2156954687","https://openalex.org/W2167212630","https://openalex.org/W2171590421","https://openalex.org/W2173027866","https://openalex.org/W2204695023","https://openalex.org/W2247119764","https://openalex.org/W2264105282","https://openalex.org/W2338373933","https://openalex.org/W2474546929","https://openalex.org/W2497965792","https://openalex.org/W2553681302","https://openalex.org/W2565684601","https://openalex.org/W2592742128","https://openalex.org/W2754595644","https://openalex.org/W2769423117","https://openalex.org/W2964113829","https://openalex.org/W6864014924"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4387478977","https://openalex.org/W4383066092","https://openalex.org/W3034267371","https://openalex.org/W4386790794"],"abstract_inverted_index":{"The":[0],"identification":[1],"of":[2,75,100,151],"drug-target":[3],"interactions":[4],"(DTIs)":[5],"is":[6,82],"a":[7,80,85,121,144],"key":[8],"task":[9],"in":[10],"drug":[11],"discovery,":[12],"where":[13,79,98],"drugs":[14],"are":[15,20,26],"chemical":[16],"compounds":[17],"and":[18,39,104,120,140],"targets":[19],"proteins.":[21],"Traditional":[22],"DTI":[23],"prediction":[24],"methods":[25],"either":[27],"time":[28],"consuming":[29],"(simulation-based":[30],"methods)":[31],"or":[32],"heavily":[33],"dependent":[34],"on":[35],"domain":[36,138],"expertise":[37],"(similarity-based":[38],"feature-based":[40],"methods).":[41],"In":[42,60,143],"this":[43],"work,":[44],"we":[45,87,147],"propose":[46],"an":[47,89],"end-to-end":[48],"neural":[49],"network":[50],"model":[51,66,114,132],"that":[52,130],"predicts":[53],"DTIs":[54],"directly":[55],"from":[56,92],"low":[57],"level":[58],"representations.":[59],"addition":[61],"to":[62,107,154,158],"making":[63],"predictions,":[64],"our":[65,113,131,152],"provides":[67],"biological":[68,156],"interpretation":[69],"using":[70,76],"two-way":[71],"attention":[72],"mechanism.":[73],"Instead":[74],"simplified":[77],"settings":[78,97],"dataset":[81,91],"evaluated":[83],"as":[84],"whole,":[86],"designed":[88],"evaluation":[90],"BindingDB":[93],"following":[94],"more":[95],"realistic":[96],"predictions":[99],"unobserved":[101],"examples":[102],"(proteins":[103],"drugs)":[105],"have":[106],"be":[108],"made.":[109],"We":[110],"experimentally":[111],"compared":[112],"with":[115],"matrix":[116],"factorization,":[117],"similarity-based":[118],"methods,":[119],"previous":[122],"deep":[123],"learning":[124],"approach.":[125],"Overall,":[126],"the":[127,149,160],"results":[128],"show":[129],"outperforms":[133],"other":[134],"approaches":[135],"without":[136],"requiring":[137],"knowledge":[139],"feature":[141],"engineering.":[142],"case":[145],"study,":[146],"illustrated":[148],"ability":[150],"approach":[153],"provide":[155],"insights":[157],"interpret":[159],"predictions.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":32},{"year":2023,"cited_by_count":40},{"year":2022,"cited_by_count":48},{"year":2021,"cited_by_count":45},{"year":2020,"cited_by_count":36},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2025-10-10T00:00:00"}
