{"id":"https://openalex.org/W7117879537","doi":"https://doi.org/10.1093/bib/bbaf676","title":"SynVerse: a modular framework for building and evaluating deep learning-based drug synergy prediction models","display_name":"SynVerse: a modular framework for building and evaluating deep learning-based drug synergy prediction models","publication_year":2025,"publication_date":"2025-11-01","ids":{"openalex":"https://openalex.org/W7117879537","doi":"https://doi.org/10.1093/bib/bbaf676","pmid":"https://pubmed.ncbi.nlm.nih.gov/41470047"},"language":"en","primary_location":{"id":"doi:10.1093/bib/bbaf676","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bib/bbaf676","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":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1093/bib/bbaf676","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011812186","display_name":"Nure Tasnina","orcid":"https://orcid.org/0009-0000-2971-0987"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nure Tasnina","raw_affiliation_strings":["Department of Computer Science, Virginia Tech , Blacksburg, VA 24060 ,"],"raw_orcid":"https://orcid.org/0009-0000-2971-0987","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Tech , Blacksburg, VA 24060 ,","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115040301","display_name":"Maryam Haghani","orcid":"https://orcid.org/0009-0006-3377-0417"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maryam Haghani","raw_affiliation_strings":["Department of Computer Science, Virginia Tech , Blacksburg, VA 24060 ,"],"raw_orcid":"https://orcid.org/0009-0006-3377-0417","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Tech , Blacksburg, VA 24060 ,","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121747508","display_name":"T M Murali","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"T M Murali","raw_affiliation_strings":["Department of Computer Science, Virginia Tech , Blacksburg, VA 24060 ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Tech , Blacksburg, VA 24060 ,","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5121747508"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":{"value":4011,"currency":"USD","value_usd":4011},"apc_paid":{"value":4011,"currency":"USD","value_usd":4011},"fwci":1.0453,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85632796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"26","issue":"6","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":0.5852000117301941,"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":0.5852000117301941,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.27649998664855957,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.04490000009536743,"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/generalizability-theory","display_name":"Generalizability theory","score":0.7890999913215637},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6567000150680542},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6319000124931335},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5494999885559082},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5005999803543091},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43880000710487366},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.391400009393692}],"concepts":[{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.7890999913215637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7178999781608582},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6567000150680542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6337000131607056},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6319000124931335},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5806000232696533},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5494999885559082},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43880000710487366},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.391400009393692},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3255999982357025},{"id":"https://openalex.org/C64903051","wikidata":"https://www.wikidata.org/wiki/Q2198549","display_name":"Drug development","level":3,"score":0.3073999881744385},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.2703999876976013}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004357","descriptor_name":"Drug Synergism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004357","descriptor_name":"Drug Synergism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004357","descriptor_name":"Drug Synergism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004357","descriptor_name":"Drug Synergism","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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1093/bib/bbaf676","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bib/bbaf676","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":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},{"id":"pmid:41470047","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41470047","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":"pmh:oai:pubmedcentral.nih.gov:12753315","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12753315/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12753315/pdf/bbaf676.pdf","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Brief Bioinform","raw_type":"Text"},{"id":"pmh:oai:europepmc.org:11563896","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12753315","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1093/bib/bbaf676","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bib/bbaf676","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":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G111080332","display_name":"Collaborative Research: BeeHive: A Cross-Problem Benchmarking Framework for Network Biology","funder_award_id":"2233967","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7545771382","display_name":null,"funder_award_id":"DBI-2233967","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1577460040","https://openalex.org/W1975147762","https://openalex.org/W1988037271","https://openalex.org/W2008840001","https://openalex.org/W2039109621","https://openalex.org/W2043398720","https://openalex.org/W2044834685","https://openalex.org/W2156737316","https://openalex.org/W2200017991","https://openalex.org/W2295598076","https://openalex.org/W2299417213","https://openalex.org/W2471562228","https://openalex.org/W2540423520","https://openalex.org/W2612467560","https://openalex.org/W2775061087","https://openalex.org/W2801555904","https://openalex.org/W2911964244","https://openalex.org/W2950182476","https://openalex.org/W2950860419","https://openalex.org/W2982291409","https://openalex.org/W3016970897","https://openalex.org/W3086347240","https://openalex.org/W3092034553","https://openalex.org/W3127930610","https://openalex.org/W3203908308","https://openalex.org/W4205719393","https://openalex.org/W4212966936","https://openalex.org/W4289315841","https://openalex.org/W4308834893","https://openalex.org/W4311247426","https://openalex.org/W4327676467","https://openalex.org/W4328048216","https://openalex.org/W4360608719","https://openalex.org/W4362657842","https://openalex.org/W4362720950","https://openalex.org/W4365816072","https://openalex.org/W4378953498","https://openalex.org/W4384818885","https://openalex.org/W4386758612","https://openalex.org/W4388845139","https://openalex.org/W4391724175","https://openalex.org/W4392500220","https://openalex.org/W4392817999","https://openalex.org/W4395689586","https://openalex.org/W4396720067","https://openalex.org/W4403256806","https://openalex.org/W4404252717","https://openalex.org/W4405248633","https://openalex.org/W4406833746","https://openalex.org/W4407751074","https://openalex.org/W4409257324","https://openalex.org/W7128190017"],"related_works":[],"abstract_inverted_index":{"Synergistic":[0],"drug":[1,25,109],"combinations":[2],"are":[3],"often":[4,35],"used":[5],"to":[6,56,73,127],"treat":[7],"cancer.":[8],"Experimental":[9],"exploration":[10],"of":[11],"all":[12],"possibilities":[13],"is":[14],"expensive.":[15],"Deep":[16],"learning":[17],"(DL)":[18],"offers":[19],"a":[20,48,69,102],"potential":[21],"alternative":[22],"for":[23,137],"predicting":[24],"pair":[26],"synergy":[27],"in":[28],"specific":[29],"cell":[30,86,111,131],"lines.":[31,132],"However,":[32],"current":[33],"methods":[34],"suffer":[36],"from":[37],"data":[38],"leakage":[39],"and":[40,61,68,85,92,114,130,147],"lack":[41],"systematic":[42],"ablation":[43,63],"studies.":[44],"We":[45,78],"propose":[46],"SynVerse,":[47],"comprehensive":[49],"evaluation":[50],"framework":[51],"featuring":[52],"four":[53],"data-splitting":[54],"strategies":[55],"assess":[57],"DL":[58],"model":[59,100],"generalizability":[60],"three":[62],"studies:":[64],"module-based,":[65],"feature":[66],"shuffling,":[67],"novel":[70],"network-based":[71],"approach":[72],"disentangle":[74],"factors":[75],"influencing":[76],"performance.":[77,121],"evaluated":[79],"sixteen":[80],"models":[81,123],"incorporating":[82],"eight":[83],"drug-":[84],"line-specific":[87],"features,":[88],"five":[89],"preprocessing":[90],"techniques,":[91],"two":[93],"encoders.":[94],"Our":[95],"analysis":[96],"revealed":[97],"that":[98],"no":[99],"outperformed":[101],"baseline":[103],"using":[104],"one-hot":[105],"encoding.":[106],"Biologically":[107],"meaningful":[108],"or":[110],"line":[112],"features":[113],"drug-drug":[115],"interactions":[116],"did":[117],"not":[118],"drive":[119],"predictive":[120],"All":[122],"showed":[124],"poor":[125],"generalization":[126],"unseen":[128],"drugs":[129],"SynVerse":[133],"highlights":[134],"the":[135],"need":[136],"substantial":[138],"improvements":[139],"before":[140],"computational":[141],"predictors":[142],"can":[143],"reliably":[144],"support":[145],"experimental":[146],"clinical":[148],"settings.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-18T08:10:14.011955","created_date":"2026-01-01T00:00:00"}
