{"id":"https://openalex.org/W3130891725","doi":"https://doi.org/10.1109/tcbb.2021.3060430","title":"Graph Convolutional Networks for Drug Response Prediction","display_name":"Graph Convolutional Networks for Drug Response Prediction","publication_year":2021,"publication_date":"2021-02-20","ids":{"openalex":"https://openalex.org/W3130891725","doi":"https://doi.org/10.1109/tcbb.2021.3060430","mag":"3130891725","pmid":"https://pubmed.ncbi.nlm.nih.gov/33606633"},"language":"en","primary_location":{"id":"doi:10.1109/tcbb.2021.3060430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbb.2021.3060430","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101867247","display_name":"Tuan Nguyen","orcid":"https://orcid.org/0000-0002-3616-5267"},"institutions":[{"id":"https://openalex.org/I138622004","display_name":"National Economics University","ror":"https://ror.org/021xbwv17","country_code":"VN","type":"education","lineage":["https://openalex.org/I138622004"]},{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU","VN"],"is_corresponding":true,"raw_author_name":"Tuan Nguyen","raw_affiliation_strings":["Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia","Faculty of Mathematical Economics, National Economics University, Hanoi, Vietnam"],"raw_orcid":"https://orcid.org/0000-0002-3616-5267","affiliations":[{"raw_affiliation_string":"Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]},{"raw_affiliation_string":"Faculty of Mathematical Economics, National Economics University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I138622004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051659582","display_name":"Giang T.T. Nguyen","orcid":"https://orcid.org/0000-0003-2098-568X"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Giang T. T. Nguyen","raw_affiliation_strings":["Network Information Center, Hanoi University of Science and Technology, Hanoi, Vietnam"],"raw_orcid":"https://orcid.org/0000-0003-2098-568X","affiliations":[{"raw_affiliation_string":"Network Information Center, Hanoi University of Science and Technology, Hanoi, Vietnam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100705489","display_name":"Thin Nguyen","orcid":"https://orcid.org/0000-0003-3467-8963"},"institutions":[{"id":"https://openalex.org/I138622004","display_name":"National Economics University","ror":"https://ror.org/021xbwv17","country_code":"VN","type":"education","lineage":["https://openalex.org/I138622004"]},{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU","VN"],"is_corresponding":false,"raw_author_name":"Thin Nguyen","raw_affiliation_strings":["Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia","Faculty of Mathematical Economics, National Economics University, Hanoi, Vietnam"],"raw_orcid":"https://orcid.org/0000-0003-3467-8963","affiliations":[{"raw_affiliation_string":"Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]},{"raw_affiliation_string":"Faculty of Mathematical Economics, National Economics University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I138622004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032004195","display_name":"Duc\u2010Hau Le","orcid":"https://orcid.org/0000-0002-4951-5916"},"institutions":[{"id":"https://openalex.org/I4210142044","display_name":"VinUniversity","ror":"https://ror.org/052dmdr17","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210142044"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Duc-Hau Le","raw_affiliation_strings":["College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam","Department of Computational Biomedicine, Vingroup Big Data Institute, Hanoi, Vietnam"],"raw_orcid":"https://orcid.org/0000-0002-4951-5916","affiliations":[{"raw_affiliation_string":"College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210142044"]},{"raw_affiliation_string":"Department of Computational Biomedicine, Vingroup Big Data Institute, Hanoi, Vietnam","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101867247"],"corresponding_institution_ids":["https://openalex.org/I138622004","https://openalex.org/I149704539"],"apc_list":null,"apc_paid":null,"fwci":15.9813,"has_fulltext":false,"cited_by_count":182,"citation_normalized_percentile":{"value":0.9934268,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"19","issue":"1","first_page":"146","last_page":"154"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.8281000256538391,"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":0.8281000256538391,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.0364999994635582,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.023000000044703484,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6839725971221924},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6768295764923096},{"id":"https://openalex.org/keywords/drug-response","display_name":"Drug response","score":0.6063140630722046},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5458807945251465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4742019474506378},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4521012306213379},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4431428909301758},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4324720501899719},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3774116039276123},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3664351999759674},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.3436632752418518},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.31231141090393066},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2656545639038086},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11579030752182007}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6839725971221924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6768295764923096},{"id":"https://openalex.org/C2994119904","wikidata":"https://www.wikidata.org/wiki/Q1251001","display_name":"Drug response","level":3,"score":0.6063140630722046},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5458807945251465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4742019474506378},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4521012306213379},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4431428909301758},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4324720501899719},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3774116039276123},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3664351999759674},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.3436632752418518},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.31231141090393066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2656545639038086},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11579030752182007},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012984","descriptor_name":"Software","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012984","descriptor_name":"Software","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012984","descriptor_name":"Software","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D023281","descriptor_name":"Genomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D023281","descriptor_name":"Genomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D023281","descriptor_name":"Genomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tcbb.2021.3060430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbb.2021.3060430","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},{"id":"pmid:33606633","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33606633","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM transactions on computational biology and bioinformatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W19078547","https://openalex.org/W1955701043","https://openalex.org/W2021383150","https://openalex.org/W2034235577","https://openalex.org/W2038227076","https://openalex.org/W2043398720","https://openalex.org/W2087312216","https://openalex.org/W2108068107","https://openalex.org/W2108933868","https://openalex.org/W2110071511","https://openalex.org/W2125789330","https://openalex.org/W2129860849","https://openalex.org/W2130942839","https://openalex.org/W2134657928","https://openalex.org/W2137983211","https://openalex.org/W2158485828","https://openalex.org/W2163605009","https://openalex.org/W2170973067","https://openalex.org/W2177317049","https://openalex.org/W2187351898","https://openalex.org/W2194775991","https://openalex.org/W2197241765","https://openalex.org/W2397757171","https://openalex.org/W2410597202","https://openalex.org/W2436108096","https://openalex.org/W2501016862","https://openalex.org/W2508784321","https://openalex.org/W2526925775","https://openalex.org/W2540540415","https://openalex.org/W2587240909","https://openalex.org/W2592742128","https://openalex.org/W2754595644","https://openalex.org/W2762742184","https://openalex.org/W2785947426","https://openalex.org/W2787055278","https://openalex.org/W2795257806","https://openalex.org/W2798788651","https://openalex.org/W2807463161","https://openalex.org/W2809216727","https://openalex.org/W2811201370","https://openalex.org/W2903886788","https://openalex.org/W2919115771","https://openalex.org/W2946099214","https://openalex.org/W2946834067","https://openalex.org/W2962711740","https://openalex.org/W2962851944","https://openalex.org/W2964015378","https://openalex.org/W2964677890","https://openalex.org/W2965750004","https://openalex.org/W2968311537","https://openalex.org/W2969085937","https://openalex.org/W3000373012","https://openalex.org/W3000469142","https://openalex.org/W3082081167","https://openalex.org/W4297733535","https://openalex.org/W4385245566","https://openalex.org/W6600744685","https://openalex.org/W6679436768","https://openalex.org/W6684191040","https://openalex.org/W6685133223","https://openalex.org/W6724219016","https://openalex.org/W6726873649","https://openalex.org/W6739901393","https://openalex.org/W6754929296","https://openalex.org/W6765898395"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W3019910406","https://openalex.org/W2747895175","https://openalex.org/W2946583009","https://openalex.org/W2614669534","https://openalex.org/W2104406636","https://openalex.org/W3202613528","https://openalex.org/W2128801478","https://openalex.org/W2105512057","https://openalex.org/W4252625449"],"abstract_inverted_index":{"BACKGROUND:":[0],"Drug":[1],"response":[2,130,203],"prediction":[3],"is":[4],"an":[5],"important":[6],"problem":[7],"in":[8,87,165],"computational":[9],"personalized":[10],"medicine.":[11],"Many":[12],"machine-learning-based":[13],"methods,":[14],"especially":[15],"deep":[16],"learning-based":[17],"ones,":[18],"have":[19],"been":[20,61],"proposed":[21],"for":[22,79,123,152,169],"this":[23,66],"task.":[24],"However,":[25],"these":[26],"methods":[27],"often":[28],"represent":[29,122],"the":[30,48,56,80,92,129,154,177,183,186,190,199],"drugs":[31,84,110,194],"as":[32,101,195],"strings,":[33],"which":[34],"are":[35,47],"not":[36,60],"a":[37,70,140],"natural":[38],"way":[39],"to":[40,55,121,189],"depict":[41],"molecules.":[42],"Also,":[43,172],"interpretation":[44],"(e.g.,":[45],"what":[46],"mutation":[49],"or":[50],"copy":[51],"number":[52],"aberration":[53],"contributing":[54],"drug":[57,202],"response)":[58],"has":[59],"considered":[62],"thoroughly.":[63],"METHODS:":[64],"In":[65,82],"study,":[67],"we":[68,181],"propose":[69],"novel":[71],"method,":[72],"GraphDRP,":[73,83],"based":[74],"on":[75],"graph":[76,147],"convolutional":[77,148],"network":[78],"problem.":[81],"were":[85,99,114,150],"represented":[86],"molecular":[88],"graphs":[89,196],"directly":[90],"capturing":[91],"bonds":[93],"among":[94],"atoms,":[95],"meanwhile":[96],"cell":[97,112],"lines":[98,113],"depicted":[100],"binary":[102],"vectors":[103],"of":[104,109,132,146,156,176,185,201,206],"genomic":[105,187],"aberrations.":[106],"Representative":[107],"features":[108,155],"and":[111,208,211],"learned":[115],"by":[116,139],"convolution":[117],"layers,":[118],"then":[119],"combined":[120],"each":[124,133],"drug-cell":[125,134],"line":[126,135],"pair.":[127],"Finally,":[128],"value":[131],"pair":[136],"was":[137],"predicted":[138],"fully-connected":[141],"neural":[142],"network.":[143],"Four":[144],"variants":[145],"networks":[149],"used":[151],"learning":[153],"drugs.":[157],"RESULTS:":[158],"We":[159],"found":[160],"that":[161],"GraphDRP":[162,179],"outperforms":[163],"tCNNS":[164],"all":[166,170],"performance":[167,200],"measures":[168],"experiments.":[171],"through":[173],"saliency":[174],"maps":[175],"resulting":[178],"models,":[180],"discovered":[182],"contribution":[184],"aberrations":[188],"responses.":[191],"CONCLUSION:":[192],"Representing":[193],"can":[197,214],"improve":[198],"prediction.":[204],"Availability":[205],"data":[207],"materials:":[209],"Data":[210],"source":[212],"code":[213],"be":[215],"downloaded":[216],"athttps://github.com/hauldhut/GraphDRP.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":22},{"year":2025,"cited_by_count":53},{"year":2024,"cited_by_count":45},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-02T09:04:35.204637","created_date":"2025-10-10T00:00:00"}