{"id":"https://openalex.org/W4390991955","doi":"https://doi.org/10.1109/bibm58861.2023.10385907","title":"Deep Learning Integration with Phenotypic Similarities and Heterogeneous Networks for Drug-Target Interaction Prediction","display_name":"Deep Learning Integration with Phenotypic Similarities and Heterogeneous Networks for Drug-Target Interaction Prediction","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390991955","doi":"https://doi.org/10.1109/bibm58861.2023.10385907"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385907","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bibm58861.2023.10385907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5026250850","display_name":"Yongtian Wang","orcid":"https://orcid.org/0000-0001-9422-0888"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongtian Wang","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361055","display_name":"Li Li","orcid":"https://orcid.org/0000-0001-8963-949X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036345096","display_name":"Yewei Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yewei Shen","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101721790","display_name":"Yizhuo Zhang","orcid":"https://orcid.org/0009-0002-9496-1007"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhuo Zhang","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015716918","display_name":"Yuhe Zhang","orcid":"https://orcid.org/0000-0002-2469-4946"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhe Zhang","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009944817","display_name":"Xuequn Shang","orcid":"https://orcid.org/0000-0002-7249-8210"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuequn Shang","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi&#x2019;an,PR China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"98","issue":null,"first_page":"2945","last_page":"2951"},"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9977999925613403,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9876000285148621,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7998790740966797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6305443048477173},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6154752373695374},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5373095273971558},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47945964336395264},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4538905918598175},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4420728385448456},{"id":"https://openalex.org/keywords/drug-target","display_name":"Drug target","score":0.4386257529258728},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42213934659957886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7998790740966797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6305443048477173},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6154752373695374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5373095273971558},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47945964336395264},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4538905918598175},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4420728385448456},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.4386257529258728},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42213934659957886},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385907","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bibm58861.2023.10385907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1647729745","https://openalex.org/W1813117265","https://openalex.org/W1855023611","https://openalex.org/W1971387816","https://openalex.org/W1998898494","https://openalex.org/W2002708055","https://openalex.org/W2069293737","https://openalex.org/W2105668062","https://openalex.org/W2122863289","https://openalex.org/W2137052779","https://openalex.org/W2142572836","https://openalex.org/W2162011385","https://openalex.org/W2165674132","https://openalex.org/W2184981123","https://openalex.org/W2534390616","https://openalex.org/W2592742128","https://openalex.org/W2623587811","https://openalex.org/W2753953057","https://openalex.org/W2896646632","https://openalex.org/W2952522777","https://openalex.org/W2953169496","https://openalex.org/W2954599614","https://openalex.org/W3085429933","https://openalex.org/W3093194543","https://openalex.org/W3128182147","https://openalex.org/W3167993868","https://openalex.org/W3211778832","https://openalex.org/W3214608846","https://openalex.org/W4229371856","https://openalex.org/W4313527139","https://openalex.org/W6636975626","https://openalex.org/W6638418335"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2082756648","https://openalex.org/W3194278305","https://openalex.org/W2611989081","https://openalex.org/W2289648981","https://openalex.org/W4230611425","https://openalex.org/W1565459987","https://openalex.org/W2731899572","https://openalex.org/W4294635752","https://openalex.org/W4304166257"],"abstract_inverted_index":{"In":[0],"the":[1,6,21,35,82,89,100,117,146,153],"field":[2],"of":[3,9,24,68,92,102,137],"drug":[4,150,160],"discovery,":[5,151],"accurate":[7],"prediction":[8,91],"drug-target":[10],"interactions":[11],"(DTIs)":[12],"is":[13],"a":[14,38,50,142],"critical":[15],"yet":[16],"challenging":[17],"task,":[18],"hindered":[19],"by":[20],"intricate":[22],"dynamics":[23],"biological":[25],"systems":[26],"and":[27,70,85,110,130,139,158],"molecular":[28],"interplay.":[29],"To":[30],"address":[31],"this,":[32],"we":[33],"propose":[34],"DTI-VGAE":[36,118,133],"model,":[37],"novel":[39],"deep":[40],"learning":[41,65],"framework":[42],"that":[43],"integrates":[44],"variational":[45],"graph":[46],"autoencoders":[47],"(VGAE)":[48],"with":[49],"multi-layer":[51],"perceptron":[52],"(MLP)":[53],"for":[54,88,155],"robust":[55],"DTI":[56,103],"prediction.":[57],"Our":[58],"approach":[59,148],"focuses":[60],"on":[61],"three":[62],"key":[63],"aspects:":[64],"distinct":[66],"representations":[67],"drugs":[69],"proteins":[71],"from":[72],"heterogeneous":[73],"networks,":[74],"constructing":[75],"Drug-Protein":[76],"Pair":[77],"(DPP)":[78],"networks":[79],"to":[80,149],"capture":[81],"complex":[83],"interactions,":[84],"employing":[86],"MLP":[87,140],"final":[90],"DTIs.":[93],"This":[94],"comprehensive":[95],"methodology":[96],"not":[97],"only":[98],"enhances":[99],"accuracy":[101],"predictions":[104],"but":[105],"also":[106],"ensures":[107],"greater":[108],"reliability":[109],"stability.":[111],"Validated":[112],"through":[113],"extensive":[114],"5-fold":[115],"cross-validation,":[116],"model":[119],"consistently":[120],"outperforms":[121],"existing":[122],"methods,":[123],"achieving":[124],"superior":[125],"average":[126],"AUROC,":[127],"AUPR":[128],"scores,":[129],"accuracy.":[131],"The":[132],"model's":[134],"innovative":[135],"integration":[136],"VGAE":[138],"offers":[141],"significant":[143],"advancement":[144],"in":[145],"computational":[147],"paving":[152],"way":[154],"more":[156],"efficient":[157],"precise":[159],"development":[161],"processes.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
