{"id":"https://openalex.org/W4379184821","doi":"https://doi.org/10.1109/access.2023.3282248","title":"Validity Improvement in MolGAN-Based Molecular Generation","display_name":"Validity Improvement in MolGAN-Based Molecular Generation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379184821","doi":"https://doi.org/10.1109/access.2023.3282248"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3282248","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3282248","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143174.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143174.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075592263","display_name":"Jiayi Fan","orcid":"https://orcid.org/0000-0002-0651-2563"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jiayi Fan","raw_affiliation_strings":["Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-0651-2563","affiliations":[{"raw_affiliation_string":"Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068547596","display_name":"Seul Ki Hong","orcid":"https://orcid.org/0009-0000-8754-0306"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seul Ki Hong","raw_affiliation_strings":["Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027140824","display_name":"YongKeun Lee","orcid":"https://orcid.org/0000-0003-0789-8354"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongkeun Lee","raw_affiliation_strings":["Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-0789-8354","affiliations":[{"raw_affiliation_string":"Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075592263"],"corresponding_institution_ids":["https://openalex.org/I118373667"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9367,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.78217558,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"58359","last_page":"58366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9997000098228455,"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/T11407","display_name":"Innovative Microfluidic and Catalytic Techniques Innovation","score":0.9697999954223633,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7140436172485352},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6372973322868347},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6327593922615051},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5402860641479492},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5266126394271851},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5253783464431763},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5174211263656616},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5140915513038635},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4339936375617981},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.41163530945777893},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2872887849807739},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1862790286540985},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.1164531409740448},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07972794771194458}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140436172485352},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6372973322868347},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6327593922615051},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5402860641479492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5266126394271851},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5253783464431763},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5174211263656616},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5140915513038635},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4339936375617981},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.41163530945777893},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2872887849807739},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1862790286540985},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.1164531409740448},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07972794771194458},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3282248","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3282248","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143174.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1d28b2679eed4e0e99cfe6e1708c5077","is_oa":true,"landing_page_url":"https://doaj.org/article/1d28b2679eed4e0e99cfe6e1708c5077","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 58359-58366 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3282248","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3282248","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143174.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321292","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542"},{"id":"https://openalex.org/F4320321294","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07"},{"id":"https://openalex.org/F4320327756","display_name":"National University of Science and Technology","ror":"https://ror.org/019vsm959"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4379184821.pdf","grobid_xml":"https://content.openalex.org/works/W4379184821.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W2080635178","https://openalex.org/W2114704115","https://openalex.org/W2806351858","https://openalex.org/W2895677720","https://openalex.org/W2896506587","https://openalex.org/W2945551948","https://openalex.org/W2980210687","https://openalex.org/W2991736596","https://openalex.org/W2994860160","https://openalex.org/W2999242200","https://openalex.org/W3042995081","https://openalex.org/W3087716567","https://openalex.org/W3089336166","https://openalex.org/W3110933132","https://openalex.org/W3112113844","https://openalex.org/W3127347132","https://openalex.org/W3152435545","https://openalex.org/W3155335252","https://openalex.org/W3181844989","https://openalex.org/W3209708391","https://openalex.org/W4210710803","https://openalex.org/W4288345983","https://openalex.org/W4297951436","https://openalex.org/W6747927160","https://openalex.org/W6763846873","https://openalex.org/W6771848067","https://openalex.org/W6793474790","https://openalex.org/W6794889692"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4391584540","https://openalex.org/W2888032422","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W2996316059","https://openalex.org/W4287117424","https://openalex.org/W4387506531"],"abstract_inverted_index":{"Designing":[0],"molecules":[1,41,53,91],"that":[2,83,95,142],"have":[3],"desired":[4],"properties":[5,35,136],"is":[6,26,42,75,123],"one":[7],"of":[8,12,46,129,164,174],"the":[9,16,43,72,84,96,106,115,120,161,172],"challenging":[10],"tasks":[11],"drug":[13],"design.":[14],"Among":[15],"many":[17],"molecular":[18,48,63,165],"generative":[19,22,49,64],"models,":[20],"a":[21,62,110],"adversarial":[23,65],"network":[24,66],"(GAN),":[25],"able":[27],"to":[28,69,159],"generate":[29],"molecule":[30],"structures":[31],"with":[32,100,171],"desirable":[33],"chemical":[34,135,176],"via":[36],"reinforcement":[37,111],"learning.":[38],"Generating":[39],"valid":[40,90],"foremost":[44],"task":[45],"any":[47],"model,":[50],"since":[51],"invalid":[52],"cannot":[54],"be":[55,154],"synthesized.":[56],"We":[57,140],"base":[58],"our":[59],"research":[60],"on":[61],"(MolGAN)":[67],"architecture":[68],"investigate":[70],"how":[71],"validity":[73,107,121,130,162],"score":[74,108,122,131,163],"influenced":[76],"in":[77,92,109,169],"different":[78],"scenarios.":[79],"First,":[80],"we":[81],"verify":[82],"Vanilla":[85,101],"GAN":[86],"structure":[87],"can":[88,103],"produce":[89],"measure,":[93],"and":[94,150,157],"reward":[97],"network,":[98],"along":[99],"GAN,":[102],"further":[104],"increase":[105],"learning":[112],"manner.":[113],"Then,":[114],"procedure":[116],"for":[117],"solely":[118],"optimizing":[119,173],"tested,":[124],"followed":[125],"by":[126],"an":[127],"assessment":[128],"maintenance":[132],"while":[133],"other":[134,175],"are":[137],"being":[138],"optimized.":[139],"found":[141],"multiple":[143],"aspects,":[144],"including":[145],"loss":[146],"functions,":[147],"hyper":[148],"parameters,":[149],"training":[151],"sequences,":[152],"must":[153],"carefully":[155],"considered":[156],"optimized":[158],"raise":[160],"generation":[166],"alone":[167],"or":[168],"concurrence":[170],"property":[177],"scores.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-05T09:01:59.212387","created_date":"2025-10-10T00:00:00"}
