{"id":"https://openalex.org/W4375868985","doi":"https://doi.org/10.1109/icassp49357.2023.10096347","title":"LE-DTA: Local Extrema Convolution for Drug Target Affinity Prediction","display_name":"LE-DTA: Local Extrema Convolution for Drug Target Affinity Prediction","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4375868985","doi":"https://doi.org/10.1109/icassp49357.2023.10096347"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096347","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10096347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5092339697","display_name":"Tanoj Langore","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Tanoj Langore","raw_affiliation_strings":["National Taiwan University (NTU),Graduate Institute of Communication Engineering,Taipei,Taiwan,10617"],"affiliations":[{"raw_affiliation_string":"National Taiwan University (NTU),Graduate Institute of Communication Engineering,Taipei,Taiwan,10617","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026870554","display_name":"Te-Cheng Hsu","orcid":"https://orcid.org/0000-0003-2686-925X"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Te-Cheng Hsu","raw_affiliation_strings":["National Tsing Hua University,Institute of Communications Engineering,Hsinchu,Taiwan,30013"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Institute of Communications Engineering,Hsinchu,Taiwan,30013","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025960594","display_name":"Yi\u2010Hsien Hsieh","orcid":"https://orcid.org/0000-0003-4942-1888"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Hsien Hsieh","raw_affiliation_strings":["National Taiwan University (NTU),Graduate Institute of Communication Engineering,Taipei,Taiwan,10617"],"affiliations":[{"raw_affiliation_string":"National Taiwan University (NTU),Graduate Institute of Communication Engineering,Taipei,Taiwan,10617","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101909683","display_name":"Che Lin","orcid":"https://orcid.org/0000-0002-4986-311X"},"institutions":[{"id":"https://openalex.org/I4210128122","display_name":"Development Center for Biotechnology","ror":"https://ror.org/02ys1c285","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I4210128122"]},{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I99613584","display_name":"National Taipei University","ror":"https://ror.org/03e29r284","country_code":"TW","type":"education","lineage":["https://openalex.org/I99613584"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Che Lin","raw_affiliation_strings":["National Taiwan University (NTU),Graduate Institute of Communication Engineering,Taipei,Taiwan,10617","Center for Computational and Systems Biology and Center for Biotechnology, NTU, Taipei, Taiwan","Department of Electrical Engineering, NTU, Taipei, Taiwan","Smart Medicine and Health Informatics Program, NTU, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University (NTU),Graduate Institute of Communication Engineering,Taipei,Taiwan,10617","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"Center for Computational and Systems Biology and Center for Biotechnology, NTU, Taipei, Taiwan","institution_ids":["https://openalex.org/I4210128122"]},{"raw_affiliation_string":"Department of Electrical Engineering, NTU, Taipei, Taiwan","institution_ids":["https://openalex.org/I99613584"]},{"raw_affiliation_string":"Smart Medicine and Health Informatics Program, NTU, Taipei, Taiwan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5092339697"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.2017,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51298327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9922999739646912,"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/T13326","display_name":"Biochemical and Structural Characterization","score":0.9855999946594238,"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/maxima-and-minima","display_name":"Maxima and minima","score":0.8197163939476013},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6135481595993042},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5467856526374817},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.4986276626586914},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47764694690704346},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4641697406768799},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4619472622871399},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.45099306106567383},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4246291518211365},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42310112714767456},{"id":"https://openalex.org/keywords/virtual-screening","display_name":"Virtual screening","score":0.4138016700744629},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3791922926902771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3723467290401459},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.36474332213401794},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35752636194229126},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34573274850845337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22318437695503235},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21523040533065796},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14283961057662964},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.12977176904678345}],"concepts":[{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.8197163939476013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6135481595993042},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5467856526374817},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4986276626586914},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47764694690704346},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4641697406768799},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4619472622871399},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.45099306106567383},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4246291518211365},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42310112714767456},{"id":"https://openalex.org/C103697762","wikidata":"https://www.wikidata.org/wiki/Q4112105","display_name":"Virtual screening","level":3,"score":0.4138016700744629},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3791922926902771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3723467290401459},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.36474332213401794},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35752636194229126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34573274850845337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22318437695503235},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21523040533065796},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14283961057662964},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.12977176904678345},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096347","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10096347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W1987730034","https://openalex.org/W2035585923","https://openalex.org/W2086286404","https://openalex.org/W2605952223","https://openalex.org/W2785947426","https://openalex.org/W2807792492","https://openalex.org/W2911871527","https://openalex.org/W2921473648","https://openalex.org/W2939208918","https://openalex.org/W2962711740","https://openalex.org/W2964015378","https://openalex.org/W2997997679","https://openalex.org/W3012652877","https://openalex.org/W3022285953","https://openalex.org/W3096561213","https://openalex.org/W3133246485","https://openalex.org/W3194218357","https://openalex.org/W4297733535","https://openalex.org/W6726873649","https://openalex.org/W6754929296","https://openalex.org/W6757634740","https://openalex.org/W6761665040"],"related_works":["https://openalex.org/W1573015311","https://openalex.org/W2889938001","https://openalex.org/W4386509167","https://openalex.org/W4362464865","https://openalex.org/W2098840560","https://openalex.org/W4302604134","https://openalex.org/W2768880727","https://openalex.org/W2621548818","https://openalex.org/W2113146994","https://openalex.org/W2073081213"],"abstract_inverted_index":{"One":[0],"of":[1,5,13,101,110],"the":[2,11,27,45,48,62,96,108,112,141,170,177],"essential":[3],"parts":[4],"drug":[6,49,55],"discovery":[7],"and":[8,32,51,61,98,129,131,138,143,173],"design":[9],"is":[10],"prediction":[12,80],"drug-target":[14],"affinity":[15],"(DTA).":[16],"Researchers":[17],"have":[18],"proposed":[19,113,121,158],"computational":[20],"approaches":[21,38],"for":[22,89,103],"predicting":[23],"DTA":[24],"to":[25,43,68],"circumvent":[26],"more":[28],"expensive":[29],"in":[30,33,125,134,165],"vivo":[31],"vitro":[34],"tests.":[35],"More":[36],"recent":[37],"employed":[39],"deep":[40],"network":[41],"architectures":[42],"obtain":[44],"features":[46],"from":[47],"molecules":[50],"protein":[52,64],"sequences.":[53],"The":[54],"compounds":[56],"are":[57],"represented":[58],"as":[59,65],"graphs":[60,102],"target":[63],"a":[66,77,132],"sequence":[67],"extract":[69],"this":[70,73],"information.":[71],"In":[72],"work,":[74],"we":[75,147,160],"develop":[76],"new":[78],"graph-based":[79],"model,":[81,159],"termed":[82],"LE-DTA,":[83],"that":[84,150],"utilizes":[85],"local":[86,97],"extrema":[87,100],"convolutions":[88],"effective":[90],"feature":[91],"extraction.":[92],"It":[93],"focuses":[94],"on":[95,115,140,156,169,176],"global":[99],"node":[104],"embedding.":[105],"We":[106],"investigated":[107],"performances":[109],"both":[111],"models":[114],"three":[116],"different":[117],"benchmark":[118],"datasets.":[119],"Our":[120],"model":[122],"showed":[123,149],"improvement":[124,175],"CI":[126],"by":[127,136,167],"1.12%":[128],"0.35%":[130],"reduction":[133,164],"MSE":[135,166],"7.7%":[137],"3.33%":[139],"KIBA":[142,171],"BindingDB":[144,178],"datasets,":[145],"respectively.":[146],"also":[148],"despite":[151],"using":[152],"various":[153],"pooling":[154],"operations":[155],"our":[157],"achieved":[161],"an":[162],"average":[163],"7%":[168],"dataset":[172],"3%":[174],"dataset.":[179]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
