{"id":"https://openalex.org/W7120056565","doi":"https://doi.org/10.1007/s10822-025-00725-x","title":"Prodrug-ML: prodrug-likeness prediction via machine learning on sampled negative decoys","display_name":"Prodrug-ML: prodrug-likeness prediction via machine learning on sampled negative decoys","publication_year":2026,"publication_date":"2026-01-10","ids":{"openalex":"https://openalex.org/W7120056565","doi":"https://doi.org/10.1007/s10822-025-00725-x","pmid":"https://pubmed.ncbi.nlm.nih.gov/41518576","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/12790554"},"language":"en","primary_location":{"id":"doi:10.1007/s10822-025-00725-x","doi":"https://doi.org/10.1007/s10822-025-00725-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10822-025-00725-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10822-025-00725-x.pdf","source":{"id":"https://openalex.org/S64621741","display_name":"Journal of Computer-Aided Molecular Design","issn_l":"0920-654X","issn":["0920-654X","1573-4951"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","doyens","jufo-1","medline","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer-Aided Molecular Design","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7120056565"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10822-025-00725-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093702622","display_name":"Sadettin Y. Ugurlu","orcid":"https://orcid.org/0000-0001-9589-0269","observed_orcids":["https://orcid.org/0000-0001-9589-0269"]},"institutions":[{"id":"https://openalex.org/I197907453","display_name":"Akdeniz University","ror":"https://ror.org/01m59r132","country_code":"TR","type":"education","lineage":["https://openalex.org/I197907453"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Sadettin Y. Ugurlu","raw_affiliation_strings":["Department of Materials Science and Engineering, Faculty of Engineering, Akdeniz University, Dumlupinar Bulvari, 07058, Antalya, Turkey","Novexus Ltd, 07058, Antalya, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Materials Science and Engineering, Faculty of Engineering, Akdeniz University, Dumlupinar Bulvari, 07058, Antalya, Turkey","institution_ids":["https://openalex.org/I197907453"]},{"raw_affiliation_string":"Novexus Ltd, 07058, Antalya, Turkey","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122406408","display_name":"Shan He","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Shan He","raw_affiliation_strings":["School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK. s.he.1@bham.ac.uk"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK. s.he.1@bham.ac.uk","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5093702622","https://openalex.org/A5122406408"],"corresponding_institution_ids":["https://openalex.org/I197907453","https://openalex.org/I79619799"],"apc_list":{"value":4190,"currency":"USD","value_usd":4190},"apc_paid":{"value":4190,"currency":"USD","value_usd":4190},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"1","first_page":"45","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.00019999999494757503,"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/T12534","display_name":"Protein Degradation and Inhibitors","score":0.0,"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/prodrugs","display_name":"prodrugs","score":0.8270000219345093},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.5580000281333923},{"id":"https://openalex.org/keywords/lead-optimization","display_name":"lead optimization","score":0.8460000157356262},{"id":"https://openalex.org/keywords/noisy-labels","display_name":"label noise","score":0.6309999823570251},{"id":"https://openalex.org/keywords/domain-bias","display_name":"domain bias","score":0.6060000061988831},{"id":"https://openalex.org/keywords/multi-model-ensemble","display_name":"multi-model ensemble","score":0.7680000066757202},{"id":"https://openalex.org/keywords/lightgbm","display_name":"LightGBM","score":0.7620000243186951},{"id":"https://openalex.org/keywords/chembl","display_name":"ChEMBL","score":0.6209999918937683},{"id":"https://openalex.org/keywords/virtual-screening","display_name":"virtual screening","score":0.5080000162124634},{"id":"https://openalex.org/keywords/chemical-diversity","display_name":"chemical diversity","score":0.43700000643730164},{"id":"https://openalex.org/keywords/drug-likeness","display_name":"drug-likeness","score":0.3240000009536743}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7111999988555908},{"id":"https://openalex.org/C108215921","wikidata":"https://www.wikidata.org/wiki/Q603741","display_name":"Prodrug","level":2,"score":0.7027999758720398},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.677299976348877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.641700029373169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.637499988079071},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.517799973487854},{"id":"https://openalex.org/C2777120189","wikidata":"https://www.wikidata.org/wiki/Q780067","display_name":"Triage","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4401000142097473},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42820000648498535},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4032999873161316},{"id":"https://openalex.org/C2775905019","wikidata":"https://www.wikidata.org/wiki/Q192572","display_name":"In silico","level":3,"score":0.3783999979496002},{"id":"https://openalex.org/C2989486834","wikidata":"https://www.wikidata.org/wiki/Q3808900","display_name":"True positive rate","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33169999718666077},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.31690001487731934},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C111771559","wikidata":"https://www.wikidata.org/wiki/Q66295","display_name":"Derivative (finance)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C2776904630","wikidata":"https://www.wikidata.org/wiki/Q356336","display_name":"Adept","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.26440000534057617},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.2515000104904175},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2500999867916107}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011355","descriptor_name":"Prodrugs","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":true},{"descriptor_ui":"D011355","descriptor_name":"Prodrugs","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1007/s10822-025-00725-x","doi":"https://doi.org/10.1007/s10822-025-00725-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10822-025-00725-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10822-025-00725-x.pdf","source":{"id":"https://openalex.org/S64621741","display_name":"Journal of Computer-Aided Molecular Design","issn_l":"0920-654X","issn":["0920-654X","1573-4951"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","doyens","jufo-1","medline","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer-Aided Molecular Design","raw_type":"journal-article"},{"id":"pmid:41518576","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41518576","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,"listed_in":[],"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":"Journal of computer-aided molecular design","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12790554","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12790554/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"J Comput Aided Mol Des","raw_type":"Text"},{"id":"pmh:oai:pure.atira.dk:openaire/848be0ea-22d0-41c1-ae04-b39c30581a33","doi":null,"is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/848be0ea-22d0-41c1-ae04-b39c30581a33","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ugurlu, S Y & He, S 2026, 'Prodrug-ML : prodrug-likeness prediction via machine learning on sampled negative decoys', Journal of Computer-Aided Molecular Design, vol. 40, no. 1, 45. https://doi.org/10.1007/s10822-025-00725-x","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s10822-025-00725-x","doi":"https://doi.org/10.1007/s10822-025-00725-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10822-025-00725-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10822-025-00725-x.pdf","source":{"id":"https://openalex.org/S64621741","display_name":"Journal of Computer-Aided Molecular Design","issn_l":"0920-654X","issn":["0920-654X","1573-4951"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","doyens","jufo-1","medline","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer-Aided Molecular Design","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5683000087738037}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7120056565.pdf","grobid_xml":"https://content.openalex.org/works/W7120056565.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W437687746","https://openalex.org/W1598849072","https://openalex.org/W1833217932","https://openalex.org/W1900824189","https://openalex.org/W1968319881","https://openalex.org/W1986959058","https://openalex.org/W2005122786","https://openalex.org/W2006381002","https://openalex.org/W2036927874","https://openalex.org/W2042110087","https://openalex.org/W2059183805","https://openalex.org/W2115062514","https://openalex.org/W2131216411","https://openalex.org/W2141842573","https://openalex.org/W2150931435","https://openalex.org/W2204950780","https://openalex.org/W2295702989","https://openalex.org/W2399536524","https://openalex.org/W2442524546","https://openalex.org/W2470942791","https://openalex.org/W2558999090","https://openalex.org/W2561838791","https://openalex.org/W2801859295","https://openalex.org/W2936503027","https://openalex.org/W2958712449","https://openalex.org/W3126031592","https://openalex.org/W3139703399","https://openalex.org/W3153061758","https://openalex.org/W3162274578","https://openalex.org/W3189436819","https://openalex.org/W3208515103","https://openalex.org/W3209295695","https://openalex.org/W4210589602","https://openalex.org/W4210716706","https://openalex.org/W4224280420","https://openalex.org/W4234944446","https://openalex.org/W4251008181","https://openalex.org/W4255796527","https://openalex.org/W4283066304","https://openalex.org/W4318305482","https://openalex.org/W4365456885","https://openalex.org/W4387603944","https://openalex.org/W4390919619","https://openalex.org/W4403681347","https://openalex.org/W4405792910","https://openalex.org/W4406229302","https://openalex.org/W4407134790","https://openalex.org/W4407808935","https://openalex.org/W4412370542","https://openalex.org/W7105536595"],"related_works":["https://openalex.org/W7095616154","https://openalex.org/W1548342851","https://openalex.org/W2897565908","https://openalex.org/W2220400398","https://openalex.org/W2158126103","https://openalex.org/W2576869235","https://openalex.org/W4388257208","https://openalex.org/W6903830881","https://openalex.org/W2094568831","https://openalex.org/W4318305482"],"abstract_inverted_index":{"A":[0],"prodrug":[1,83,134,305],"is":[2],"a":[3,290,304],"pharmacologically":[4],"inactive":[5],"(or":[6],"attenuated)":[7],"derivative":[8],"that":[9,97,330],"undergoes":[10],"bioreversible":[11],"transformation":[12],"in":[13,38,76,320],"vivo":[14],"to":[15,60,131,161,173],"release":[16],"an":[17,90,234],"active":[18],"parent":[19,146],"drug,":[20],"enabling":[21],"temporary":[22],"optimization":[23],"of":[24,35,46,71,120,240,312],"properties":[25],"such":[26,175],"as":[27],"solubility,":[28],"permeability,":[29],"and":[30,65,114,126,155,201,208,216,233,253,269,284,323],"targeting.":[31],"Despite":[32],"expanding":[33],"catalogs":[34],"known":[36],"prodrugs,":[37],"silico":[39],"screening":[40,84],"remains":[41],"limited":[42],"by":[43,189],"the":[44,69,178,182,244,246,307,333],"absence":[45],"reliable":[47,72],"negative":[48,195],"examples:":[49],"training/evaluation":[50],"sets":[51],"often":[52],"contain":[53],"only":[54,158,332],"positives":[55],"or":[56,141],"ad-hoc":[57],"decoys,":[58,212],"leading":[59],"class":[61],"imbalance,":[62],"property-mismatch":[63],"shortcuts,":[64],"irreproducible":[66],"benchmarks.":[67],"Unfortunately,":[68],"limitation":[70],"negatives":[73],"has":[74,225],"resulted":[75],"there":[77],"being":[78],"no":[79],"efficient":[80,91],"machine":[81,92],"learning-based":[82,93],"approach.":[85],"Therefore,":[86],"we":[87],"introduce":[88],"Prodrug-ML,":[89,154],"screen":[94],"for":[95],"prodrug-likeness":[96],"prioritizes":[98],"candidates":[99,160],"rather":[100],"than":[101],"asserting":[102],"mechanistic":[103],"truth.":[104],"Prodrug-ML":[105,179],"helps":[106],"medicinal":[107],"chemists":[108],"triage":[109],"prodrugging":[110],"ideas":[111],"during":[112],"hit-to-lead":[113],"lead":[115],"optimization,":[116],"filter":[117],"enumerated":[118],"libraries":[119],"promoiety-attachment":[121],"variants":[122],"before":[123],"ADMET":[124],"assays,":[125],"retrospectively":[127],"mine":[128],"internal/ChEMBL-like":[129],"collections":[130],"surface":[132],"likely":[133],"chemotypes.":[135],"In":[136,171,243],"practice,":[137],"users":[138],"(i)":[139,190],"generate":[140],"collect":[142],"candidate":[143],"structures":[144],"(e.g.,":[145],"drug":[147],"\u00b1":[148],"pro-moieties),":[149],"(ii)":[150,205],"score":[151],"them":[152],"with":[153,220,300],"(iii)":[156,213],"advance":[157],"high-scoring":[159],"synthesis/assay,":[162],"thereby":[163],"reducing":[164],"wet-lab":[165,328],"load":[166],"while":[167],"maintaining":[168],"chemical":[169],"diversity.":[170],"order":[172],"achieve":[174],"practical":[176],"usage,":[177],"framework,":[180],"containing":[181],"default":[183],"classifier,":[184],"LightGBM,":[185],"addresses":[186],"these":[187,292],"issues":[188],"constructing":[191],"three":[192],"complementary,":[193],"property-controlled":[194],"cohorts":[196],"(DUD-E-style":[197],"near-misses,":[198],"random":[199],"ChEMBL,":[200],"strictly":[202],"filtered":[203],"ChEMBL),":[204],"hardness":[206],"control":[207],"label-noise":[209],"guardrails":[210],"on":[211,230],"domain-bias":[214],"control,":[215],"(iv)":[217],"cross-decoy":[218],"validation":[219],"multimodel":[221,247],"feature":[222],"selection.":[223],"Produg-ML":[224],"been":[226],"evaluated":[227],"five":[228],"times":[229],"hold-out":[231],"data":[232],"unseen":[235],"test":[236],"benchmark,":[237],"after":[238],"80%":[239],"training":[241],"data.":[242],"benchmarks,":[245],"ensemble":[248],"consistently":[249],"improves":[250],"early":[251,334],"retrieval":[252],"overall":[254],"discrimination,":[255],"attaining":[256],"[Formula:":[257,260,263,266,270,276,281,286,309,316],"see":[258,261,264,267,271,277,282,287,310,317],"text],":[259,262,265,268,272,278,283],"alongside":[273],"ROC":[274],"AUC":[275],"average":[279],"precision":[280],"F1":[285],"text].":[288],"As":[289],"result,":[291],"results,":[293],"especially":[294],"high":[295],"BEDROC":[296],"scores,":[297],"are":[298],"consistent":[299],"concentrating":[301],"at":[302],"least":[303],"within":[306],"top":[308],"text]":[311,318],"ranked":[313],"candidates,":[314],"implying":[315],"reductions":[319],"experimental":[321],"time":[322],"cost":[324],"when":[325],"using":[326],"standard":[327],"workflows":[329],"assay":[331],"tranche.":[335]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-01-10T00:00:00"}