{"id":"https://openalex.org/W7131628294","doi":"https://doi.org/10.1186/s12859-026-06374-7","title":"Semisupervised approach for dominant gene selection and classification","display_name":"Semisupervised approach for dominant gene selection and classification","publication_year":2026,"publication_date":"2026-02-26","ids":{"openalex":"https://openalex.org/W7131628294","doi":"https://doi.org/10.1186/s12859-026-06374-7","pmid":"https://pubmed.ncbi.nlm.nih.gov/41749075"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-026-06374-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-026-06374-7","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC 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/10.1186/s12859-026-06374-7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007209532","display_name":"Reshma Rastogi","orcid":null},"institutions":[{"id":"https://openalex.org/I90425906","display_name":"South Asian University","ror":"https://ror.org/02kjyst95","country_code":"IN","type":"education","lineage":["https://openalex.org/I90425906"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Reshma Rastogi","raw_affiliation_strings":["MLSI Lab, Dept. of Computer Science and Engineering, South Asian University, Rajpur Road, Maidan Garhi, 110068, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0002-9322-4251","affiliations":[{"raw_affiliation_string":"MLSI Lab, Dept. of Computer Science and Engineering, South Asian University, Rajpur Road, Maidan Garhi, 110068, New Delhi, India","institution_ids":["https://openalex.org/I90425906"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036549754","display_name":"Mamta Bhattarai Lamsal","orcid":"https://orcid.org/0009-0000-1490-8034"},"institutions":[{"id":"https://openalex.org/I90425906","display_name":"South Asian University","ror":"https://ror.org/02kjyst95","country_code":"IN","type":"education","lineage":["https://openalex.org/I90425906"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Mamta Bhattarai Lamsal","raw_affiliation_strings":["MLSI Lab, Dept. of Computer Science and Engineering, South Asian University, Rajpur Road, Maidan Garhi, 110068, New Delhi, India. mamta@students.sau.ac.in"],"raw_orcid":"https://orcid.org/0009-0000-1490-8034","affiliations":[{"raw_affiliation_string":"MLSI Lab, Dept. of Computer Science and Engineering, South Asian University, Rajpur Road, Maidan Garhi, 110068, New Delhi, India. mamta@students.sau.ac.in","institution_ids":["https://openalex.org/I90425906"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5036549754"],"corresponding_institution_ids":["https://openalex.org/I90425906"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15038087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.8163999915122986,"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.8163999915122986,"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"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.08449999988079071,"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"}},{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.023499999195337296,"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/dna-microarray","display_name":"DNA microarray","score":0.5679000020027161},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5368000268936157},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5157999992370605},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5077999830245972},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.498199999332428},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47519999742507935},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.42160001397132874},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.39739999175071716},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.3962000012397766}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6258999705314636},{"id":"https://openalex.org/C95371953","wikidata":"https://www.wikidata.org/wiki/Q591745","display_name":"DNA microarray","level":4,"score":0.5679000020027161},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5425000190734863},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5368000268936157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5209000110626221},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5157999992370605},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.498199999332428},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47519999742507935},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.4287000000476837},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.4278999865055084},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.42160001397132874},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C2984324147","wikidata":"https://www.wikidata.org/wiki/Q3080021","display_name":"Gene selection","level":5,"score":0.35670000314712524},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.3490999937057495},{"id":"https://openalex.org/C18431079","wikidata":"https://www.wikidata.org/wiki/Q1502169","display_name":"Gene expression profiling","level":4,"score":0.33239999413490295},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.322299987077713},{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.2833999991416931},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27970001101493835},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.27889999747276306},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.27239999175071716},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.26030001044273376},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.25209999084472656}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000098429","descriptor_name":"Classification Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098429","descriptor_name":"Classification Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005799","descriptor_name":"Genes, Dominant","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005799","descriptor_name":"Genes, Dominant","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":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12859-026-06374-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-026-06374-7","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:41749075","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41749075","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":"BMC bioinformatics","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:c683dc764ca643af8e63d59d46f8df28","is_oa":false,"landing_page_url":"https://doaj.org/article/c683dc764ca643af8e63d59d46f8df28","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 27, Iss 1 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13041400","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13041400/","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,"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-026-06374-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-026-06374-7","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W150175414","https://openalex.org/W1964939988","https://openalex.org/W1968261842","https://openalex.org/W2010243889","https://openalex.org/W2083162467","https://openalex.org/W2087684630","https://openalex.org/W2101386839","https://openalex.org/W2113590298","https://openalex.org/W2128873747","https://openalex.org/W2143426320","https://openalex.org/W2154053567","https://openalex.org/W2344681634","https://openalex.org/W2466653524","https://openalex.org/W2598351993","https://openalex.org/W2752352959","https://openalex.org/W2793446582","https://openalex.org/W2879929106","https://openalex.org/W2963876460","https://openalex.org/W2973129849","https://openalex.org/W3016774208","https://openalex.org/W3133744637","https://openalex.org/W3138479716","https://openalex.org/W3151033386","https://openalex.org/W3186962463","https://openalex.org/W4220682410","https://openalex.org/W4245645788","https://openalex.org/W4285315255","https://openalex.org/W4286266907","https://openalex.org/W4361292005","https://openalex.org/W4363646104","https://openalex.org/W4387868962","https://openalex.org/W4392301565","https://openalex.org/W4405529379"],"related_works":[],"abstract_inverted_index":{"BACKGROUND:":[0],"Semisupervised":[1],"learning":[2,41,52,205],"has":[3],"attracted":[4],"significant":[5],"interest":[6],"in":[7,50,131,185,213],"gene":[8,70,156,186,196,208],"expression":[9,157,187],"analysis":[10,118],"due":[11],"to":[12,15,42,79,111],"its":[13],"ability":[14],"improve":[16],"classification":[17,73,113,191,212],"performance":[18,164,192],"under":[19],"limited":[20,179],"labeled":[21,180],"data,":[22],"a":[23,65,103],"common":[24],"challenge":[25],"arising":[26],"from":[27],"high":[28,183],"dimensionality":[29,184],"and":[30,72,86,101,115,127,137,182,193,210],"small":[31],"sample":[32],"sizes.":[33],"Existing":[34],"semisupervised":[35,66,204],"methods":[36],"often":[37],"rely":[38],"on":[39,107,152],"manifold":[40],"propagate":[43],"label":[44,48,99],"information;":[45],"however,":[46],"weak":[47],"connections":[49],"early":[51],"stages":[53],"can":[54],"reduce":[55],"their":[56],"effectiveness.":[57],"RESULTS:":[58],"To":[59],"address":[60],"these":[61],"limitations,":[62],"we":[63],"propose":[64],"approach":[67],"for":[68,98,206],"dominant":[69,207],"selection":[71],"(SADGSC)":[74],"that":[75,160],"employs":[76],"feature":[77],"decomposition":[78],"identify":[80],"essential":[81],"features":[82],"while":[83],"suppressing":[84],"noise":[85],"redundancy.":[87],"The":[88,170],"proposed":[89,171],"method":[90],"adopts":[91],"hinge":[92],"loss":[93,97],"instead":[94],"of":[95,119,145,178,203],"square":[96],"prediction":[100],"constructs":[102],"projection":[104],"matrix":[105],"based":[106],"confidence-weighted":[108],"features,":[109],"leading":[110],"improved":[112],"accuracy":[114],"interpretability.":[116],"Biological":[117],"the":[120,142,146,176,201],"top-ranked":[121],"genes":[122],"(e.g.,":[123],"PGR,":[124],"KRT14,":[125],"TOX3,":[126],"FGF10)":[128],"reveals":[129],"enrichment":[130],"hormone":[132],"signaling":[133],"epithelial-mesenchymal":[134],"transition,":[135],"apoptosis,":[136],"oxidative":[138],"stress":[139],"pathways,":[140],"demonstrating":[141],"biological":[143,215],"relevance":[144],"selected":[147],"genes.":[148],"Experimental":[149],"evaluations":[150],"conducted":[151],"eleven":[153],"datasets,":[154,158],"primarily":[155],"show":[159],"SADGSC":[161,172],"achieves":[162],"competitive":[163],"compared":[165],"with":[166],"state-of-the-art":[167],"methods.":[168],"CONCLUSIONS:":[169],"framework":[173],"effectively":[174],"addresses":[175],"challenges":[177],"data":[181],"analysis,":[188],"providing":[189],"strong":[190],"biologically":[194],"meaningful":[195],"selection.":[197],"These":[198],"findings":[199],"highlight":[200],"potential":[202],"discovery":[209],"robust":[211],"high-dimensional":[214],"datasets.":[216]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-02-27T00:00:00"}
