{"id":"https://openalex.org/W7120269064","doi":"https://doi.org/10.48550/arxiv.2601.05151","title":"ROOFS: RObust biOmarker Feature Selection","display_name":"ROOFS: RObust biOmarker Feature Selection","publication_year":2026,"publication_date":"2026-01-08","ids":{"openalex":"https://openalex.org/W7120269064","doi":"https://doi.org/10.48550/arxiv.2601.05151"},"language":"en","primary_location":{"id":"pmh:doi:10.48550/arxiv.2601.05151","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bakhmach, Anastasiia","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bakhmach, Anastasiia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049094278","display_name":"Paul Dufoss\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dufoss\u00e9, Paul","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072189706","display_name":"A. Vaglio","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vaglio, Andrea","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104387342","display_name":"Florence Monville","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Monville, Florence","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122469100","display_name":"Laurent Greillier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Greillier, Laurent","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122579008","display_name":"Fabrice Barl\u00e9si","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barl\u00e9si, Fabrice","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063987547","display_name":"S\u00e9bastien Benzekry","orcid":"https://orcid.org/0000-0002-3749-8637"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benzekry, S\u00e9bastien","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10158","display_name":"Cancer Immunotherapy and Biomarkers","score":0.28139999508857727,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10158","display_name":"Cancer Immunotherapy and Biomarkers","score":0.28139999508857727,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.18610000610351562,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12576","display_name":"vaccines and immunoinformatics approaches","score":0.06759999692440033,"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/feature-selection","display_name":"Feature selection","score":0.6820999979972839},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5821999907493591},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5205000042915344},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4756999909877777},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.43140000104904175},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4269999861717224},{"id":"https://openalex.org/keywords/biomarker-discovery","display_name":"Biomarker discovery","score":0.41990000009536743},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.39590001106262207},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.38749998807907104}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6820999979972839},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5950000286102295},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5821999907493591},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5476999878883362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5227000117301941},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5205000042915344},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5063999891281128},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4756999909877777},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.43140000104904175},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C124535831","wikidata":"https://www.wikidata.org/wiki/Q4915074","display_name":"Biomarker discovery","level":4,"score":0.41990000009536743},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C2781197716","wikidata":"https://www.wikidata.org/wiki/Q864574","display_name":"Biomarker","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C61722155","wikidata":"https://www.wikidata.org/wiki/Q6667643","display_name":"Logistic model tree","level":3,"score":0.3156999945640564},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.25279998779296875},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:doi:10.48550/arxiv.2601.05151","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:HAL:hal-05241230v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-05241230","pdf_url":null,"source":{"id":"https://openalex.org/S4406922454","display_name":"SPIRE - Sciences Po Institutional REpository","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"Preprints, Working Papers, ..."},{"id":"doi:10.48550/arxiv.2601.05151","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.05151","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2601.05151","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Feature":[0,83],"selection":[1],"(FS)":[2],"is":[3],"essential":[4],"for":[5],"biomarker":[6],"discovery":[7,206],"and":[8,23,61,75,114,137,140,195,211,242],"clinical":[9,163,248],"predictive":[10,126],"modeling.":[11],"Over":[12],"the":[13,96,111,154,161,178,201,215,233,237,244],"past":[14],"decades,":[15],"methodological":[16,36,73],"literature":[17],"on":[18,110,145,158,200],"FS":[19,65,99,108,180,240],"has":[20,38,232],"become":[21],"rich":[22],"mature,":[24],"offering":[25],"a":[26,85,118,149,197],"wide":[27],"spectrum":[28],"of":[29,34,98,121,134,156,169,203,239,247],"algorithmic":[30],"approaches.":[31],"However,":[32],"much":[33],"this":[35,70],"progress":[37],"not":[39],"fully":[40],"translated":[41],"into":[42],"applied":[43],"biomedical":[44,50],"research.":[45],"Moreover,":[46],"challenges":[47],"inherent":[48],"in":[49,95,174,183,188],"data,":[51],"such":[52],"as":[53,214],"high-dimensional":[54],"feature":[55],"space,":[56],"low":[57],"sample":[58],"size,":[59],"multicollinearity,":[60],"missing":[62],"values,":[63],"make":[64],"non-trivial.":[66],"To":[67],"help":[68,93],"bridge":[69],"gap":[71],"between":[72],"development":[74],"practical":[76],"application,":[77],"we":[78,185],"propose":[79],"ROOFS":[80,105,157,231],"(RObust":[81],"biOmarker":[82],"Selection),":[84],"Python":[86],"package":[87],"available":[88],"at":[89,166],"https://gitlab.inria.fr/compo/roofs,":[90],"designed":[91],"to":[92,102,171,235],"researchers":[94],"choice":[97],"method":[100],"adapted":[101],"their":[103],"problem.":[104],"benchmarks":[106],"multiple":[107],"methods":[109,181,220],"user's":[112],"data":[113,147,159],"generates":[115],"reports":[116],"summarizing":[117],"comprehensive":[119,228],"set":[120],"evaluation":[122],"metrics,":[123],"including":[124,221],"downstream":[125],"performance":[127],"estimated":[128],"using":[129],"optimism":[130],"correction,":[131],"stability,":[132],"robustness":[133],"individual":[135],"features,":[136],"true":[138],"positive":[139,142],"false":[141,205],"rates":[143],"assessed":[144],"semi-synthetic":[146],"with":[148,190,230],"simulated":[150],"outcome.":[151],"We":[152,225],"demonstrate":[153],"utility":[155],"from":[160,209],"PIONeeR":[162],"trial,":[164],"aimed":[165],"identifying":[167],"predictors":[168],"resistance":[170],"anti-PD-(L)1":[172],"immunotherapy":[173],"lung":[175],"cancer.":[176],"Of":[177],"34":[179],"gathered":[182],"ROOFS,":[184],"evaluated":[186],"23":[187],"combination":[189],"11":[191],"classifiers":[192],"(253":[193],"models)":[194],"identified":[196],"filter":[198],"based":[199],"union":[202],"Benjamini-Hochberg":[204],"rate-adjusted":[207],"p-values":[208],"t-test":[210],"logistic":[212],"regression":[213],"optimal":[216],"approach,":[217],"outperforming":[218],"other":[219],"widely":[222],"used":[223],"LASSO.":[224],"conclude":[226],"that":[227],"benchmarking":[229],"potential":[234],"improve":[236],"reproducibility":[238],"discoveries":[241],"increase":[243],"translational":[245],"value":[246],"models.":[249]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-01-10T00:00:00"}
