{"id":"https://openalex.org/W7171559135","doi":"https://doi.org/10.1145/3807503.3819360","title":"CB-Gene: A Computational\u2013Biological Framework for Gene Prioritization in High-Dimensional-Low-Sample-Size (HDLSS) Lymphoma Data","display_name":"CB-Gene: A Computational\u2013Biological Framework for Gene Prioritization in High-Dimensional-Low-Sample-Size (HDLSS) Lymphoma Data","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7171559135","doi":"https://doi.org/10.1145/3807503.3819360"},"language":null,"primary_location":{"id":"doi:10.1145/3807503.3819360","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819360","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3807503.3819360","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110936297","display_name":"Shamima Naznin","orcid":null},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Shamima Naznin","raw_affiliation_strings":["Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh"],"raw_orcid":"https://orcid.org/0000-0003-4601-9631","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100733249","display_name":"Mohammad Saifur Rahman","orcid":"https://orcid.org/0000-0002-9887-4456"},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"M Saifur Rahman","raw_affiliation_strings":["Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh"],"raw_orcid":"https://orcid.org/0000-0002-9887-4456","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183697816"],"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/prioritization","display_name":"Prioritization","score":0.5297999978065491},{"id":"https://openalex.org/keywords/lymphoma","display_name":"Lymphoma","score":0.4058000147342682},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.35280001163482666},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.29409998655319214},{"id":"https://openalex.org/keywords/human-genome","display_name":"Human genome","score":0.27900001406669617}],"concepts":[{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.5123999714851379},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.487199991941452},{"id":"https://openalex.org/C2779338263","wikidata":"https://www.wikidata.org/wiki/Q208414","display_name":"Lymphoma","level":2,"score":0.4058000147342682},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.3305000066757202},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.32910001277923584},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29019999504089355},{"id":"https://openalex.org/C197077220","wikidata":"https://www.wikidata.org/wiki/Q720988","display_name":"Human genome","level":4,"score":0.27900001406669617},{"id":"https://openalex.org/C141231307","wikidata":"https://www.wikidata.org/wiki/Q7020","display_name":"Genome","level":3,"score":0.27639999985694885},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3807503.3819360","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819360","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3807503.3819360","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819360","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1493357981","https://openalex.org/W2048415203","https://openalex.org/W2069620150","https://openalex.org/W2089353165","https://openalex.org/W2092421078","https://openalex.org/W2100980426","https://openalex.org/W2471304467","https://openalex.org/W2811460725","https://openalex.org/W2945250061","https://openalex.org/W2995602901","https://openalex.org/W3004823408","https://openalex.org/W3005520922","https://openalex.org/W3084074548","https://openalex.org/W3205039941","https://openalex.org/W3216978859","https://openalex.org/W4206486197","https://openalex.org/W4220654285","https://openalex.org/W4224222011","https://openalex.org/W4226298065","https://openalex.org/W4290973443","https://openalex.org/W4294732935","https://openalex.org/W4302363010","https://openalex.org/W4315874454","https://openalex.org/W4319322340","https://openalex.org/W4385075196","https://openalex.org/W4387964911","https://openalex.org/W4388793533","https://openalex.org/W4393194052","https://openalex.org/W4399540542"],"related_works":[],"abstract_inverted_index":{"Lymphatic":[0],"malignancies,":[1],"particularly":[2],"diffuse":[3],"large":[4],"B-cell":[5],"lymphoma":[6,60],"(DLBCL),":[7],"are":[8,106,128],"driven":[9],"by":[10],"intricate":[11],"genetic":[12],"and":[13,77,84,91,126,137,139,186],"molecular":[14],"disruptions":[15],"that":[16,80,103,147],"can":[17],"be":[18],"systematically":[19,51],"explored":[20],"through":[21,96],"gene":[22,57],"expression":[23,67],"profiling.":[24],"DLBCL":[25],"gene-expression":[26],"dataset":[27],"measures":[28],"thousands":[29],"of":[30,162,178],"genes,":[31],"yet":[32],"only":[33],"a":[34,75,206],"small":[35],"subset":[36],"is":[37,49],"truly":[38],"disease-relevant.":[39],"Although":[40],"numerous":[41],"computational":[42,200],"methods":[43],"report":[44],"high":[45],"classification":[46],"accuracy,":[47],"there":[48],"no":[50],"integrated":[52],"computational-biological":[53],"validation":[54,101],"framework":[55],"for":[56,209],"prioritization":[58],"in":[59,181,193,212],"using":[61],"high-dimensional":[62],"Low":[63],"sample":[64],"size":[65],"(HDLSS)":[66],"data.":[68],"To":[69],"address":[70],"this":[71,196],"gap,":[72],"we":[73,114],"propose":[74],"robust":[76],"interpretable":[78],"pipeline":[79],"combines":[81],"nature-inspired":[82],"optimization":[83],"machine":[85],"learning":[86],"to":[87],"prioritize":[88],"lymphoma-associated":[89],"genes":[90,105,117,149,180],"validate":[92],"their":[93,191],"functional":[94],"relevance":[95],"pathway":[97],"enrichment":[98],"analysis.":[99],"Functional":[100],"reveals":[102],"these":[104,148,179],"significantly":[107],"associated":[108],"with":[109,159,202],"lymphoma-related":[110],"biological":[111,167,203],"processes.":[112],"Notably":[113],"found":[115],"that,":[116],"such":[118],"as":[119],"MCM2,":[120],"MCM3,":[121],"MCM6,":[122],"MCM7,":[123],"CDK1,":[124],"KIF11,":[125],"CCT3":[127],"consistently":[129],"enriched":[130],"across":[131],"multiple":[132],"pathways,":[133],"including":[134],"B":[135],"lymphoblasts":[136],"Haematopoietic":[138],"Lymphoid":[140],"Tissue":[141],"cell":[142],"lines.":[143],"Our":[144],"findings":[145],"show":[146],"do":[150],"more":[151],"than":[152],"classify":[153],"cancer":[154],"(achieved":[155],"95.56%":[156],"test-validation":[157],"accuracy":[158],"an":[160],"F-measure":[161],"0.961);":[163],"they":[164],"reflect":[165],"the":[166,175],"mechanisms":[168],"underlying":[169],"lymphoma.":[170],"Tissue-specific":[171],"analysis":[172],"further":[173],"validates":[174],"clinical":[176],"significance":[177],"lymph":[182],"nodes,":[183],"erythroid":[184],"cells,":[185],"B-lymphoblastoid":[187],"cells":[188],"-":[189],"supporting":[190],"role":[192],"lymphomagenesis.":[194],"Overall,":[195],"integrative":[197],"approach":[198],"bridges":[199],"precision":[201],"interpretation,":[204],"offering":[205],"powerful":[207],"tool":[208],"biomarker":[210],"discovery":[211],"hematologic":[213],"oncology.":[214]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2026-07-29T00:00:00"}
