{"id":"https://openalex.org/W4389725003","doi":"https://doi.org/10.1109/clei60451.2023.10346152","title":"Machine Learning Modeling Predicting Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) Inhibitors Structure-Activity Relationships Using Quantum DFT Descriptors","display_name":"Machine Learning Modeling Predicting Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) Inhibitors Structure-Activity Relationships Using Quantum DFT Descriptors","publication_year":2023,"publication_date":"2023-10-16","ids":{"openalex":"https://openalex.org/W4389725003","doi":"https://doi.org/10.1109/clei60451.2023.10346152"},"language":"en","primary_location":{"id":"doi:10.1109/clei60451.2023.10346152","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/clei60451.2023.10346152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 XLIX Latin American Computer Conference (CLEI)","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/A5104213710","display_name":"Jos\u00e9 Abreu Salas","orcid":null},"institutions":[{"id":"https://openalex.org/I130194489","display_name":"University of Alicante","ror":"https://ror.org/05t8bcz72","country_code":"ES","type":"education","lineage":["https://openalex.org/I130194489"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Jos\u00e9 Abreu Salas","raw_affiliation_strings":["Instituto Universitario de Investigaci&#x00F3;n Inform&#x00E1;tica, Universidad de Alicante,Alicante,Espa&#x00F1;a"],"affiliations":[{"raw_affiliation_string":"Instituto Universitario de Investigaci&#x00F3;n Inform&#x00E1;tica, Universidad de Alicante,Alicante,Espa&#x00F1;a","institution_ids":["https://openalex.org/I130194489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068097526","display_name":"Roberto Espinosa","orcid":"https://orcid.org/0000-0001-7875-4951"},"institutions":[{"id":"https://openalex.org/I185652977","display_name":"University of Tarapac\u00e1","ror":"https://ror.org/04xe01d27","country_code":"CL","type":"education","lineage":["https://openalex.org/I185652977"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Roberto Espinosa Oliva","raw_affiliation_strings":["Universidad de Tarapac&#x00E1;,Departamento de Ingenier&#x00ED;a en Computaci&#x00F3;n e Inform&#x00E1;tica,Arica,Chile"],"affiliations":[{"raw_affiliation_string":"Universidad de Tarapac&#x00E1;,Departamento de Ingenier&#x00ED;a en Computaci&#x00F3;n e Inform&#x00E1;tica,Arica,Chile","institution_ids":["https://openalex.org/I185652977"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068205537","display_name":"Pedro Mirabal","orcid":"https://orcid.org/0000-0001-7345-6007"},"institutions":[{"id":"https://openalex.org/I2802558902","display_name":"Universidad Cat\u00f3lica de Temuco","ror":"https://ror.org/051nvp675","country_code":"CL","type":"education","lineage":["https://openalex.org/I2802558902"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Pedro Mirabal","raw_affiliation_strings":["Unversidad Cat&#x00F3;lica de Temuco,Departamento de Ingenier&#x00ED;a Inform&#x00E1;tica,Temuco,Chile"],"affiliations":[{"raw_affiliation_string":"Unversidad Cat&#x00F3;lica de Temuco,Departamento de Ingenier&#x00ED;a Inform&#x00E1;tica,Temuco,Chile","institution_ids":["https://openalex.org/I2802558902"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043699939","display_name":"Emilio Lamazares","orcid":"https://orcid.org/0000-0002-4878-1892"},"institutions":[{"id":"https://openalex.org/I172787465","display_name":"University of Concepci\u00f3n","ror":"https://ror.org/0460jpj73","country_code":"CL","type":"education","lineage":["https://openalex.org/I172787465"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Emilio Lamazares","raw_affiliation_strings":["Universidad de Concepci&#x00F3;n,Pathophysiology Department,Concepci&#x00F3;n,Chile"],"affiliations":[{"raw_affiliation_string":"Universidad de Concepci&#x00F3;n,Pathophysiology Department,Concepci&#x00F3;n,Chile","institution_ids":["https://openalex.org/I172787465"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093489271","display_name":"Karel Mena-Ulacia","orcid":null},"institutions":[{"id":"https://openalex.org/I2802558902","display_name":"Universidad Cat\u00f3lica de Temuco","ror":"https://ror.org/051nvp675","country_code":"CL","type":"education","lineage":["https://openalex.org/I2802558902"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Karel Mena-Ulacia","raw_affiliation_strings":["Universidad Cat&#x00F3;lica de Temuco,Departamento de Ciencias Biol&#x00F3;gicas y Qu&#x00ED;micas,Temuco,Chile"],"affiliations":[{"raw_affiliation_string":"Universidad Cat&#x00F3;lica de Temuco,Departamento de Ciencias Biol&#x00F3;gicas y Qu&#x00ED;micas,Temuco,Chile","institution_ids":["https://openalex.org/I2802558902"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5104213710"],"corresponding_institution_ids":["https://openalex.org/I130194489"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24677221,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9973999857902527,"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":0.9973999857902527,"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":0.9379000067710876,"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/T13489","display_name":"Synthesis of \u03b2-Lactam Compounds","score":0.9088000059127808,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"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/vegf-receptors","display_name":"VEGF receptors","score":0.5251383781433105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.523402750492096},{"id":"https://openalex.org/keywords/kinase-insert-domain-receptor","display_name":"Kinase insert domain receptor","score":0.43771976232528687},{"id":"https://openalex.org/keywords/vascular-endothelial-growth-factor","display_name":"Vascular endothelial growth factor","score":0.3911615312099457},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.37851250171661377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3399147093296051},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.32973265647888184},{"id":"https://openalex.org/keywords/vascular-endothelial-growth-factor-a","display_name":"Vascular endothelial growth factor A","score":0.26961246132850647},{"id":"https://openalex.org/keywords/cancer-research","display_name":"Cancer research","score":0.25422683358192444},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.1838511824607849}],"concepts":[{"id":"https://openalex.org/C167734588","wikidata":"https://www.wikidata.org/wiki/Q4356503","display_name":"VEGF receptors","level":2,"score":0.5251383781433105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.523402750492096},{"id":"https://openalex.org/C14858245","wikidata":"https://www.wikidata.org/wiki/Q18028241","display_name":"Kinase insert domain receptor","level":5,"score":0.43771976232528687},{"id":"https://openalex.org/C2777025900","wikidata":"https://www.wikidata.org/wiki/Q29725","display_name":"Vascular endothelial growth factor","level":3,"score":0.3911615312099457},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.37851250171661377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3399147093296051},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.32973265647888184},{"id":"https://openalex.org/C146285616","wikidata":"https://www.wikidata.org/wiki/Q7916455","display_name":"Vascular endothelial growth factor A","level":4,"score":0.26961246132850647},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","level":1,"score":0.25422683358192444},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.1838511824607849}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/clei60451.2023.10346152","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/clei60451.2023.10346152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 XLIX Latin American Computer Conference (CLEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G1278878422","display_name":null,"funder_award_id":"8729-20","funder_id":"https://openalex.org/F4320324327","funder_display_name":"Universidad de Tarapac\u00e1"},{"id":"https://openalex.org/G5557875299","display_name":null,"funder_award_id":"11180650","funder_id":"https://openalex.org/F4320338073","funder_display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320324327","display_name":"Universidad de Tarapac\u00e1","ror":"https://ror.org/04xe01d27"},{"id":"https://openalex.org/F4320338073","display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","ror":"https://ror.org/02ap3w078"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W232876404","https://openalex.org/W1530159724","https://openalex.org/W1965173894","https://openalex.org/W1966885459","https://openalex.org/W1978449177","https://openalex.org/W1981368803","https://openalex.org/W1988010020","https://openalex.org/W1994941357","https://openalex.org/W2000840224","https://openalex.org/W2006441761","https://openalex.org/W2009458392","https://openalex.org/W2019687329","https://openalex.org/W2026835783","https://openalex.org/W2028046413","https://openalex.org/W2033757486","https://openalex.org/W2043737771","https://openalex.org/W2044202126","https://openalex.org/W2049062021","https://openalex.org/W2067718414","https://openalex.org/W2069258346","https://openalex.org/W2081065649","https://openalex.org/W2084630618","https://openalex.org/W2101646342","https://openalex.org/W2101958915","https://openalex.org/W2113056062","https://openalex.org/W2125283600","https://openalex.org/W2130479394","https://openalex.org/W2153833372","https://openalex.org/W2163646378","https://openalex.org/W2173733785","https://openalex.org/W2188588602","https://openalex.org/W2193742729","https://openalex.org/W2531345670","https://openalex.org/W2623293810","https://openalex.org/W2739439285","https://openalex.org/W2768191586","https://openalex.org/W2801991413","https://openalex.org/W2911812451","https://openalex.org/W2943824340","https://openalex.org/W2945181390","https://openalex.org/W2963305393","https://openalex.org/W2967351647","https://openalex.org/W2971084756","https://openalex.org/W2980885134","https://openalex.org/W2987296346","https://openalex.org/W2987346547","https://openalex.org/W2997833137","https://openalex.org/W3003025448","https://openalex.org/W3004429200","https://openalex.org/W3005450478","https://openalex.org/W3010062792","https://openalex.org/W3016054986","https://openalex.org/W3028239487","https://openalex.org/W3031591723","https://openalex.org/W3080117955","https://openalex.org/W3084873012","https://openalex.org/W3085068776","https://openalex.org/W3115697098","https://openalex.org/W3165722314","https://openalex.org/W3210709863","https://openalex.org/W4211217388","https://openalex.org/W4236058936","https://openalex.org/W4239510810","https://openalex.org/W4284677512","https://openalex.org/W6609126827","https://openalex.org/W6687423370","https://openalex.org/W6688612899","https://openalex.org/W7047381192"],"related_works":["https://openalex.org/W4307908351","https://openalex.org/W4254185523","https://openalex.org/W2076049271","https://openalex.org/W2413160507","https://openalex.org/W2384535579","https://openalex.org/W2407035760","https://openalex.org/W629251600","https://openalex.org/W4238800710","https://openalex.org/W3146004296","https://openalex.org/W2170701819"],"abstract_inverted_index":{"The":[0,156],"vascular":[1],"endothelial":[2,15],"growth":[3],"factor":[4],"receptor":[5,21],"2":[6,80],"(VEGFR2)":[7],"is":[8,22,60],"considered":[9],"the":[10,46,53,74,100,116,136,146,167],"most":[11,148],"important":[12],"marker":[13],"for":[14,73,99,108,166],"cell":[16],"development.":[17],"In":[18,67],"particular,":[19],"this":[20,68],"directly":[23],"related":[24],"to":[25],"tumor":[26],"angiogenesis":[27],"regulation.":[28],"Therefore,":[29],"several":[30],"inhibitors":[31,50],"of":[32,38,48,119,130,164],"VEGFR-2":[33],"are":[34,40],"developed,":[35],"and":[36,83,95,122,135],"many":[37],"them":[39],"now":[41],"in":[42,64,101,115,124],"clinical":[43],"trials.":[44],"For":[45],"design":[47],"new":[49],"against":[51],"VEGFR2,":[52],"half-maximal":[54],"inhibitory":[55],"concentration":[56],"<tex":[57,70],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[58,71],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(IC_{50})$</tex>":[59],"a":[61,141],"core":[62],"step":[63],"pharmacological":[65],"research.":[66],"work,":[69],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$IC_{50}$</tex>":[72],"Vascular":[75],"Endothelial":[76],"Growth":[77],"Factor":[78],"Receptor":[79],"was":[81,85,106,140],"studied,":[82],"it":[84],"modeled":[86],"using":[87],"eleven":[88],"Machine":[89,110],"Learning":[90,111],"Algorithms.":[91],"Thirteen":[92],"molecular":[93],"descriptors":[94,150],"fingerprints":[96],"were":[97,133],"employed":[98],"silico":[102],"modeling.":[103],"Hyper-parameter":[104],"tuning":[105],"performed":[107],"each":[109],"Algorithm,":[112],"which":[113],"helped":[114],"proper":[117],"selection":[118],"parameter":[120],"values":[121],"resulted":[123],"improved":[125],"classification":[126],"performance.":[127],"A":[128],"total":[129],"6678828":[131],"models":[132],"evaluated,":[134],"best":[137,157],"model":[138,158],"obtained":[139],"Decision":[142],"Tree":[143],"generated":[144],"from":[145,152],"three":[147],"relevant":[149],"derived":[151],"Density":[153],"Functional":[154],"Theory.":[155],"achieved":[159],"an":[160],"average":[161],"balanced":[162],"accuracy":[163],"0.75":[165],"5-fold":[168],"cross-validation.":[169]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}
