{"id":"https://openalex.org/W4377236462","doi":"https://doi.org/10.1145/3581807.3581860","title":"Inferring Potential Drug-Target Interactions using Multiple Similarities and Network Consistency Projection","display_name":"Inferring Potential Drug-Target Interactions using Multiple Similarities and Network Consistency Projection","publication_year":2022,"publication_date":"2022-11-17","ids":{"openalex":"https://openalex.org/W4377236462","doi":"https://doi.org/10.1145/3581807.3581860"},"language":"en","primary_location":{"id":"doi:10.1145/3581807.3581860","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581807.3581860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition","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/A5016379027","display_name":"Jianhua Li","orcid":"https://orcid.org/0000-0001-9261-8374"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianhua Li","raw_affiliation_strings":["College of Medicine and Biological Information Engineering, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0001-9261-8374","affiliations":[{"raw_affiliation_string":"College of Medicine and Biological Information Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764056","display_name":"Haoran Ren","orcid":"https://orcid.org/0000-0001-5864-1183"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Ren","raw_affiliation_strings":["College of Medicine and Biological Information Engineering, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0001-5864-1183","affiliations":[{"raw_affiliation_string":"College of Medicine and Biological Information Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000670180","display_name":"D. Xiao","orcid":"https://orcid.org/0000-0001-5401-6866"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dayu Xiao","raw_affiliation_strings":["College of Medicine and Biological Information Engineering, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0001-5401-6866","affiliations":[{"raw_affiliation_string":"College of Medicine and Biological Information Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081184790","display_name":"Botao Deng","orcid":"https://orcid.org/0000-0003-4080-5471"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Botao Deng","raw_affiliation_strings":["College of Medicine and Biological Information Engineering, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0003-4080-5471","affiliations":[{"raw_affiliation_string":"College of Medicine and Biological Information Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016379027"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22902956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"368","last_page":"373"},"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9668999910354614,"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":0.9448000192642212,"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/similarity","display_name":"Similarity (geometry)","score":0.6877248287200928},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6430844068527222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6388108730316162},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5521164536476135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5288406610488892},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4656079113483429},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.46311914920806885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45956116914749146},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45507776737213135},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4359775185585022},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4163222014904022},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39844369888305664},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3496019244194031},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2294589877128601},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13051080703735352}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6877248287200928},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6430844068527222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6388108730316162},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5521164536476135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5288406610488892},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4656079113483429},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.46311914920806885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45956116914749146},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45507776737213135},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4359775185585022},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4163222014904022},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39844369888305664},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3496019244194031},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2294589877128601},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13051080703735352},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581807.3581860","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581807.3581860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W363319864","https://openalex.org/W1979537657","https://openalex.org/W2106029302","https://openalex.org/W2135007932","https://openalex.org/W2153838454","https://openalex.org/W2463430624","https://openalex.org/W2537429907","https://openalex.org/W2612835976","https://openalex.org/W2753550436","https://openalex.org/W2774596167","https://openalex.org/W3000043291","https://openalex.org/W3017271475","https://openalex.org/W3095387731","https://openalex.org/W3158868742","https://openalex.org/W3188463051","https://openalex.org/W3199618438","https://openalex.org/W3202335653","https://openalex.org/W3208556307","https://openalex.org/W4224135296","https://openalex.org/W6673585231"],"related_works":["https://openalex.org/W2384408398","https://openalex.org/W2375370983","https://openalex.org/W2369557298","https://openalex.org/W2545232906","https://openalex.org/W2011212036","https://openalex.org/W2065131986","https://openalex.org/W3044685708","https://openalex.org/W4229068138","https://openalex.org/W2127643120","https://openalex.org/W1545294102"],"abstract_inverted_index":{"Developing":[0],"new":[1,9,18],"drugs":[2,13,24,41,79],"is":[3],"time-consuming,":[4],"labor-intensive":[5],"and":[6,25,42,80,117,131,150,159],"costly.":[7],"Identifying":[8],"targets":[10,81],"for":[11,39,55,65],"existing":[12],"can":[14],"help":[15],"to":[16,126],"discover":[17],"potential":[19],"therapeutic":[20],"uses":[21],"of":[22,29,78,97,134],"old":[23],"reduce":[26],"the":[27,128,151],"cost":[28],"drug":[30,100,104,107],"development.":[31],"Drug-target":[32],"interactions":[33,87],"are":[34],"usually":[35],"inferred":[36],"by":[37,88,138],"searching":[38],"similar":[40],"targets.":[43],"Various":[44],"biomedical":[45],"databases":[46],"have":[47],"been":[48],"established":[49],"currently,":[50],"which":[51],"provide":[52],"effective":[53,158],"data":[54],"predicting":[56],"drug-target":[57,86,136],"interactions.":[58],"We":[59,122],"proposed":[60],"a":[61,147],"novel":[62],"computational":[63,152],"model":[64],"discovering":[66],"Drug-Target":[67],"Interactions":[68],"using":[69],"Network":[70],"consistency":[71,140],"project":[72],"(DTIN).":[73],"The":[74],"Gaussian":[75,89,108,119],"kernel":[76,90,109,120],"similarity":[77,130],"were":[82],"derived":[83],"from":[84],"known":[85],"function,":[91],"thus":[92],"DTIN":[93,156],"incorporated":[94],"six":[95],"types":[96],"similarities,":[98],"including":[99],"chemical":[101],"structure":[102],"similarity,":[103,106,110,113,116],"ATC":[105],"target":[111,114,118],"sequence":[112],"function":[115],"similarity.":[121],"used":[123],"logistic":[124],"regression":[125],"process":[127],"integrated":[129],"predicted":[132],"scores":[133],"interacting":[135],"pairs":[137],"network":[139],"projection.":[141],"Five-fold":[142],"cross-validation":[143],"was":[144,157],"implemented":[145],"on":[146],"benchmark":[148],"dataset,":[149],"results":[153],"demonstrated":[154],"that":[155],"outperformed":[160],"two":[161],"advanced":[162],"models.":[163]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}