{"id":"https://openalex.org/W2167197582","doi":"https://doi.org/10.1109/icsmc.2009.5346852","title":"Recognition of drug-target interaction patterns using genetic algorithm-optimized Bayesian-regularized neural networks and support vector machines","display_name":"Recognition of drug-target interaction patterns using genetic algorithm-optimized Bayesian-regularized neural networks and support vector machines","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W2167197582","doi":"https://doi.org/10.1109/icsmc.2009.5346852","mag":"2167197582"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2009.5346852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","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/A5029378374","display_name":"Michael Fern\u00e1ndez","orcid":"https://orcid.org/0000-0003-2273-733X"},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Michael Fernandez","raw_affiliation_strings":["Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033360131","display_name":"Akinori Sarai","orcid":null},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akinori Sarai","raw_affiliation_strings":["Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028328692","display_name":"Shandar Ahmad","orcid":"https://orcid.org/0000-0002-7287-305X"},"institutions":[{"id":"https://openalex.org/I4210086383","display_name":"National Institute of Biomedical Innovation, Health and Nutrition","ror":"https://ror.org/001rkbe13","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210086383"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shandar Ahmad","raw_affiliation_strings":["National Institute of Biomedical Innovation, Ibaraki, Osaka, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Biomedical Innovation, Ibaraki, Osaka, Japan","institution_ids":["https://openalex.org/I4210086383"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029378374"],"corresponding_institution_ids":["https://openalex.org/I207014233"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.18907935,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"12","issue":null,"first_page":"498","last_page":"503"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.762543797492981},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7440053224563599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.606043815612793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.605513870716095},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5892547965049744},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5869970917701721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5269739627838135},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5181180834770203},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5143426656723022},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4992866516113281},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.45404118299484253},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4455728828907013},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.41741621494293213},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3740260899066925},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21703693270683289}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.762543797492981},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7440053224563599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.606043815612793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.605513870716095},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5892547965049744},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5869970917701721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5269739627838135},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5181180834770203},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5143426656723022},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4992866516113281},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.45404118299484253},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4455728828907013},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.41741621494293213},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3740260899066925},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21703693270683289},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2009.5346852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1595796962","https://openalex.org/W1970526996","https://openalex.org/W1974166884","https://openalex.org/W1974187953","https://openalex.org/W1994067502","https://openalex.org/W2011886501","https://openalex.org/W2026610312","https://openalex.org/W2040351166","https://openalex.org/W2040459007","https://openalex.org/W2043613591","https://openalex.org/W2046776694","https://openalex.org/W2047585439","https://openalex.org/W2056308182","https://openalex.org/W2063060349","https://openalex.org/W2072592565","https://openalex.org/W2081994754","https://openalex.org/W2084157271","https://openalex.org/W2108162114","https://openalex.org/W2111051539","https://openalex.org/W2119821739","https://openalex.org/W2123636872","https://openalex.org/W2130994761","https://openalex.org/W2134350696","https://openalex.org/W2139212933","https://openalex.org/W2153635508","https://openalex.org/W2164165673","https://openalex.org/W2175970307","https://openalex.org/W2911546748","https://openalex.org/W2951256269","https://openalex.org/W3120421331","https://openalex.org/W3193477162","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W3106461837","https://openalex.org/W4364381099","https://openalex.org/W3168182983","https://openalex.org/W4321472004","https://openalex.org/W4387079005","https://openalex.org/W4283700523","https://openalex.org/W2968265130","https://openalex.org/W4221166418","https://openalex.org/W2973085194","https://openalex.org/W3117893869"],"abstract_inverted_index":{"Genetic":[0],"algorithm":[1],"(GA)":[2],"applied":[3],"to":[4,47,50],"feature":[5,94],"selection":[6,34,95],"and":[7,23,39,45,60,66,82,106],"model":[8],"optimization":[9],"improved":[10],"the":[11,40,89,104,110,115,119],"performance":[12],"of":[13,35,42,69,99,109],"robust":[14,83],"mathematical":[15],"models":[16,87],"such":[17],"as":[18],"Bayesian-regularized":[19],"neural":[20],"networks":[21],"(BRANNs)":[22],"support":[24],"vector":[25],"machines":[26],"(SVMs)":[27],"on":[28,88],"different":[29],"drug":[30],"design":[31],"datasets.":[32,91],"The":[33,77],"optimum":[36,48],"input":[37],"variables":[38],"adjustment":[41],"network":[43],"weights":[44],"biases":[46],"values":[49],"yield":[51],"generalizable":[52],"predictors":[53,78],"were":[54,71,79],"optimized":[55],"by":[56,74],"combining":[57],"Bayesian":[58],"training":[59],"GA":[61,75],"based-variable":[62],"selection.":[63],"Similarly,":[64],"kernel":[65],"regularization":[67],"parameters":[68],"SVMs":[70],"properly":[72],"set":[73],"optimization.":[76],"more":[80],"accurate":[81],"than":[84],"previous":[85],"published":[86],"same":[90],"In":[92],"addition,":[93],"over":[96],"large":[97],"pools":[98],"molecular":[100],"descriptors":[101],"allowed":[102],"determining":[103],"structural":[105],"atomic":[107],"properties":[108],"ligands":[111],"that":[112],"are":[113],"ruling":[114],"biological":[116],"interactions":[117],"with":[118],"target.":[120]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
