{"id":"https://openalex.org/W3212089476","doi":"https://doi.org/10.1093/bib/bbac050","title":"SPLDExtraTrees: robust machine learning approach for predicting kinase inhibitor resistance","display_name":"SPLDExtraTrees: robust machine learning approach for predicting kinase inhibitor resistance","publication_year":2022,"publication_date":"2022-02-03","ids":{"openalex":"https://openalex.org/W3212089476","doi":"https://doi.org/10.1093/bib/bbac050","mag":"3212089476","pmid":"https://pubmed.ncbi.nlm.nih.gov/35262669"},"language":"en","primary_location":{"id":"doi:10.1093/bib/bbac050","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac050","pdf_url":null,"source":{"id":"https://openalex.org/S91767247","display_name":"Briefings in Bioinformatics","issn_l":"1467-5463","issn":["1467-5463","1477-4054"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/abs/2111.08008","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085127108","display_name":"Ziyi Yang","orcid":"https://orcid.org/0000-0002-3550-9283"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zi-Yi Yang","raw_affiliation_strings":["Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","TENCENT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"TENCENT","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052352053","display_name":"Zhaofeng Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao-Feng Ye","raw_affiliation_strings":["Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","TENCENT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"TENCENT","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040226555","display_name":"Yijia Xiao","orcid":"https://orcid.org/0000-0002-5512-3070"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi-Jia Xiao","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China","Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008663435","display_name":"Chang\u2010Yu Hsieh","orcid":"https://orcid.org/0000-0002-6242-4218"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chang-Yu Hsieh","raw_affiliation_strings":["Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","TENCENT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"TENCENT","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Sheng-Yu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sheng-Yu Zhang","raw_affiliation_strings":["Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Quantum Laboratory, Shenzhen, 518057, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008663435"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":{"value":4011,"currency":"USD","value_usd":4011},"apc_paid":null,"fwci":0.2651,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51612059,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"23","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9943000078201294,"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/T10521","display_name":"RNA and protein synthesis mechanisms","score":0.9889000058174133,"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/overfitting","display_name":"Overfitting","score":0.8612950444221497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7752038240432739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6958927512168884},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.594826877117157},{"id":"https://openalex.org/keywords/mutation","display_name":"Mutation","score":0.5255730748176575},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.18955156207084656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12511128187179565},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.10296344757080078}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8612950444221497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7752038240432739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6958927512168884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.594826877117157},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.5255730748176575},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.18955156207084656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12511128187179565},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.10296344757080078},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009154","descriptor_name":"Mutation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009154","descriptor_name":"Mutation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009154","descriptor_name":"Mutation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D056004","descriptor_name":"Molecular Dynamics Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D056004","descriptor_name":"Molecular Dynamics Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D056004","descriptor_name":"Molecular Dynamics Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1093/bib/bbac050","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac050","pdf_url":null,"source":{"id":"https://openalex.org/S91767247","display_name":"Briefings in Bioinformatics","issn_l":"1467-5463","issn":["1467-5463","1477-4054"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},{"id":"pmid:35262669","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35262669","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":"Briefings in bioinformatics","raw_type":null},{"id":"mag:3212089476","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.08008","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2111.08008","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2111.08008","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"mag:3212089476","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.08008","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6299999952316284,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1549816642","https://openalex.org/W1939721728","https://openalex.org/W1966701961","https://openalex.org/W1974324284","https://openalex.org/W1974903851","https://openalex.org/W1979107490","https://openalex.org/W1985286834","https://openalex.org/W1995137594","https://openalex.org/W2023490488","https://openalex.org/W2023921624","https://openalex.org/W2024311320","https://openalex.org/W2025816743","https://openalex.org/W2092387745","https://openalex.org/W2100913937","https://openalex.org/W2103459989","https://openalex.org/W2109363337","https://openalex.org/W2116079122","https://openalex.org/W2122307113","https://openalex.org/W2125359610","https://openalex.org/W2131487381","https://openalex.org/W2131987814","https://openalex.org/W2132984949","https://openalex.org/W2134967712","https://openalex.org/W2138019504","https://openalex.org/W2139447954","https://openalex.org/W2144288821","https://openalex.org/W2144692687","https://openalex.org/W2147993766","https://openalex.org/W2153080167","https://openalex.org/W2154670681","https://openalex.org/W2161605421","https://openalex.org/W2172034373","https://openalex.org/W2296073425","https://openalex.org/W2324374958","https://openalex.org/W2329374371","https://openalex.org/W2404459885","https://openalex.org/W2550887636","https://openalex.org/W2592643813","https://openalex.org/W2606439133","https://openalex.org/W2613362156","https://openalex.org/W2729007679","https://openalex.org/W2780523853","https://openalex.org/W2782314838","https://openalex.org/W2794930605","https://openalex.org/W2899829877","https://openalex.org/W2903836900","https://openalex.org/W2951718918","https://openalex.org/W2967710850","https://openalex.org/W2970711760","https://openalex.org/W2973418100","https://openalex.org/W3002058234","https://openalex.org/W3011469361","https://openalex.org/W3037203467","https://openalex.org/W3043934334","https://openalex.org/W3044914774","https://openalex.org/W3117622225","https://openalex.org/W3119533938","https://openalex.org/W3123446037","https://openalex.org/W3137067752","https://openalex.org/W3213922610","https://openalex.org/W6680618887","https://openalex.org/W6767761916"],"related_works":["https://openalex.org/W11644230","https://openalex.org/W8078895","https://openalex.org/W3889012","https://openalex.org/W12970924","https://openalex.org/W14024944","https://openalex.org/W18270676","https://openalex.org/W13088575","https://openalex.org/W12234377","https://openalex.org/W3035590","https://openalex.org/W1454762"],"abstract_inverted_index":{"Drug":[0],"resistance":[1,228],"is":[2,28,33],"a":[3,11,34,52,131,161],"major":[4],"threat":[5],"to":[6,30,90,197],"the":[7,15,49,55,64,68,102,154,177,199,204,218,221],"global":[8],"health":[9],"and":[10,20,54,67,107,112,149,169,173,179,186,232,242],"significant":[12],"concern":[13],"throughout":[14],"clinical":[16,69],"treatment":[17],"of":[18,44,60,93,119,220,239],"diseases":[19],"drug":[21,31,39,53,65,124],"development.":[22],"The":[23,215],"mutation":[24,148],"in":[25],"proteins":[26,209],"that":[27,73,164,238],"related":[29],"binding":[32,143],"common":[35],"cause":[36],"for":[37,63,122,210,224],"adaptive":[38],"resistance.":[40,125],"Therefore,":[41],"quantitative":[42],"estimations":[43],"how":[45],"mutations":[46],"would":[47,58],"affect":[48],"interaction":[50],"between":[51,182],"target":[56],"protein":[57,99,147],"be":[59,91],"vital":[61],"significance":[62],"development":[66],"practice.":[70],"Computational":[71],"methods":[72,86,244],"rely":[74],"on":[75,208],"molecular":[76,240],"dynamics":[77,241],"simulations,":[78],"Rosetta":[79,243],"protocols,":[80],"as":[81,83],"well":[82],"machine":[84,120,133,200],"learning":[85,121,134,201],"have":[87,115],"been":[88],"proven":[89],"capable":[92],"predicting":[94,225],"ligand":[95,142],"affinity":[96,144],"changes":[97,145],"upon":[98,146],"mutation.":[100],"However,":[101],"severely":[103],"limited":[104],"sample":[105,183],"size":[106],"heavy":[108],"noise":[109],"induced":[110],"overfitting":[111],"generalization":[113],"issues":[114],"impeded":[116],"wide":[117],"adoption":[118],"studying":[123],"In":[126,189],"this":[127],"paper,":[128],"we":[129,191],"propose":[130],"robust":[132],"method,":[135],"termed":[136],"SPLDExtraTrees,":[137],"which":[138],"can":[139],"accurately":[140],"predict":[141],"identify":[150],"resistance-causing":[151],"mutations.":[152],"Especially,":[153],"proposed":[155,222],"method":[156,223],"ranks":[157],"training":[158],"data":[159],"following":[160],"specific":[162],"scheme":[163],"starts":[165],"with":[166,203,237,245],"easy-to-learn":[167],"samples":[168,175],"gradually":[170],"incorporates":[171],"harder":[172],"diverse":[174],"into":[176],"training,":[178],"then":[180],"iterates":[181],"weight":[184],"recalculations":[185],"model":[187,202],"updates.":[188],"addition,":[190],"calculate":[192],"additional":[193],"physics-based":[194],"structural":[195],"features":[196],"provide":[198],"valuable":[205],"domain":[206],"knowledge":[207],"these":[211],"data-limited":[212],"predictive":[213,234],"tasks.":[214],"experiments":[216],"substantiate":[217],"capability":[219],"kinase":[226],"inhibitor":[227],"under":[229],"three":[230],"scenarios":[231],"achieve":[233],"accuracy":[235],"comparable":[236],"much":[246],"less":[247],"computational":[248],"costs.":[249]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
