{"id":"https://openalex.org/W3004552537","doi":"https://doi.org/10.1109/bibm47256.2019.8983181","title":"HNEDTI: Prediction of drug-target interaction based on heterogeneous network embedding","display_name":"HNEDTI: Prediction of drug-target interaction based on heterogeneous network embedding","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3004552537","doi":"https://doi.org/10.1109/bibm47256.2019.8983181","mag":"3004552537"},"language":"en","primary_location":{"id":"doi:10.1109/bibm47256.2019.8983181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5081430592","display_name":"Zhangli Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangli Lu","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","School of Computer Science and Engineering, Central South University, Changsha, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075435414","display_name":"Yake Wang","orcid":"https://orcid.org/0000-0002-0521-2876"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yake Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","School of Computer Science and Engineering, Central South University, Changsha, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033885404","display_name":"Min Zeng","orcid":"https://orcid.org/0000-0002-1726-0955"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zeng","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","School of Computer Science and Engineering, Central South University, Changsha, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100719013","display_name":"Min Li","orcid":"https://orcid.org/0000-0002-0188-1394"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Li","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","School of Computer Science and Engineering, Central South University, Changsha, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"211","last_page":"214"},"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":0.9912999868392944,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9739999771118164,"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":0.7022974491119385},{"id":"https://openalex.org/keywords/drug-target","display_name":"Drug target","score":0.6523294448852539},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6213234663009644},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5850863456726074},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5680961608886719},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5493901371955872},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.5331622362136841},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5298663973808289},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.526362955570221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5197921991348267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5129777789115906},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.4995908737182617},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.49642664194107056},{"id":"https://openalex.org/keywords/interaction-network","display_name":"Interaction network","score":0.4745664894580841},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.4423857033252716},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41321954131126404},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3797529935836792},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.33729201555252075},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.20499593019485474},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10786816477775574},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.07741892337799072}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7022974491119385},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.6523294448852539},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6213234663009644},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5850863456726074},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5680961608886719},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5493901371955872},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.5331622362136841},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5298663973808289},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.526362955570221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5197921991348267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5129777789115906},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.4995908737182617},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.49642664194107056},{"id":"https://openalex.org/C55105296","wikidata":"https://www.wikidata.org/wiki/Q841382","display_name":"Interaction network","level":3,"score":0.4745664894580841},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.4423857033252716},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41321954131126404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3797529935836792},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.33729201555252075},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.20499593019485474},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10786816477775574},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.07741892337799072},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm47256.2019.8983181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1971106435","https://openalex.org/W1972863608","https://openalex.org/W1979537657","https://openalex.org/W1984014392","https://openalex.org/W1984084871","https://openalex.org/W2018518196","https://openalex.org/W2029348196","https://openalex.org/W2048565304","https://openalex.org/W2066201825","https://openalex.org/W2074814295","https://openalex.org/W2087064593","https://openalex.org/W2099754222","https://openalex.org/W2109991441","https://openalex.org/W2132820240","https://openalex.org/W2133610472","https://openalex.org/W2153838454","https://openalex.org/W2154896031","https://openalex.org/W2161607603","https://openalex.org/W2165240999","https://openalex.org/W2165674132","https://openalex.org/W2166550586","https://openalex.org/W2259538443","https://openalex.org/W2751900761","https://openalex.org/W2793303269","https://openalex.org/W2912802963","https://openalex.org/W2935275081","https://openalex.org/W2971405760","https://openalex.org/W6749466839"],"related_works":["https://openalex.org/W2444288055","https://openalex.org/W2264671791","https://openalex.org/W2295730657","https://openalex.org/W2623587811","https://openalex.org/W2509838516","https://openalex.org/W1971106435","https://openalex.org/W2008235780","https://openalex.org/W2133776184","https://openalex.org/W2177411254","https://openalex.org/W2106029302"],"abstract_inverted_index":{"Identifying":[0],"drug-target":[1,37,42,56,86,140],"interactions":[2,38,87],"(DTIs)":[3],"is":[4,27],"an":[5,143],"important":[6],"task":[7],"in":[8],"drug":[9],"discovery.":[10],"Various":[11],"computational":[12],"models":[13],"have":[14],"been":[15],"proposed":[16],"to":[17,32,54,131,135],"predict":[18,34,55,136],"potential":[19,36],"association":[20],"between":[21],"drugs":[22,66,100,126],"and":[23,84,101,107,127,155],"targets.":[24],"However,":[25],"it":[26],"still":[28],"a":[29,49,89],"great":[30],"challenge":[31],"accurately":[33],"the":[35,62,77,111,138,164],"with":[39,72],"rare":[40],"known":[41,85],"interactions.":[43],"In":[44],"this":[45],"work,":[46],"we":[47,75],"propose":[48],"heterogeneous":[50,90,112],"network":[51,83,113],"embedding":[52],"model":[53,134],"interactions,":[57],"called":[58],"HNEDTI.":[59],"Based":[60],"on":[61,147],"assumption":[63],"that":[64,159],"similar":[65,68],"share":[67],"patterns":[69],"of":[70,99,110,117,125],"relationships":[71],"target":[73],"proteins,":[74],"integrate":[76],"drug-drug":[78],"similarity":[79,82],"network,":[80],"target-target":[81],"into":[88],"network.":[91],"HNEDTI":[92,162],"can":[93],"learn":[94],"more":[95],"accurate":[96],"feature":[97,122],"representation":[98,123],"targets":[102,128],"by":[103],"extract":[104],"both":[105],"local":[106],"global":[108],"information":[109],"from":[114],"different":[115],"lengths":[116],"meta-paths.":[118],"The":[119,145],"low":[120],"dimensional":[121],"vectors":[124],"are":[129],"applied":[130],"random":[132],"forest":[133],"whether":[137],"given":[139],"pair":[141],"has":[142],"interaction.":[144],"evaluation":[146],"four":[148],"benchmark":[149],"datasets":[150],"(Enzyme,":[151],"Ion":[152],"Channel,":[153],"GPCR":[154],"Nuclear":[156],"Receptor)":[157],"shows":[158],"our":[160],"method":[161],"outperforms":[163],"previous":[165],"methods.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}