{"id":"https://openalex.org/W2749610595","doi":"https://doi.org/10.1145/3107411.3110412","title":"Heuristic Algorithms for Feature Selection under Bayesian Models with Block-diagonal Covariance Structure","display_name":"Heuristic Algorithms for Feature Selection under Bayesian Models with Block-diagonal Covariance Structure","publication_year":2017,"publication_date":"2017-08-20","ids":{"openalex":"https://openalex.org/W2749610595","doi":"https://doi.org/10.1145/3107411.3110412","mag":"2749610595"},"language":"en","primary_location":{"id":"doi:10.1145/3107411.3110412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3107411.3110412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058611663","display_name":"Ali Foroughi pour","orcid":"https://orcid.org/0000-0002-3547-0796"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ali Foroughi pour","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037999551","display_name":"Lori A. Dalton","orcid":"https://orcid.org/0000-0001-8715-5723"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lori A. Dalton","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058611663"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09224535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"758","last_page":"759"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9966999888420105,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9878000020980835,"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/covariance","display_name":"Covariance","score":0.6622174978256226},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.659091055393219},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6109586358070374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6106001734733582},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5969956517219543},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5529322624206543},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5329139232635498},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5199819207191467},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47388285398483276},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47019800543785095},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4482437074184418},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.44608843326568604},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.436116099357605},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42889389395713806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3734591007232666},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23629280924797058},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08419689536094666}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6622174978256226},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.659091055393219},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6109586358070374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6106001734733582},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5969956517219543},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5529322624206543},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5329139232635498},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5199819207191467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47388285398483276},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47019800543785095},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4482437074184418},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.44608843326568604},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.436116099357605},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42889389395713806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3734591007232666},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23629280924797058},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08419689536094666},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3107411.3110412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3107411.3110412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2344427966","display_name":null,"funder_award_id":"CCF-1422631","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7400560131","display_name":null,"funder_award_id":"CCF-1453563","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":1,"referenced_works":["https://openalex.org/W2142846876"],"related_works":["https://openalex.org/W2788344745","https://openalex.org/W2062336688","https://openalex.org/W2910677864","https://openalex.org/W2046078371","https://openalex.org/W2383820648","https://openalex.org/W4245445763","https://openalex.org/W2380784125","https://openalex.org/W3162209258","https://openalex.org/W3004057759","https://openalex.org/W2889085215"],"abstract_inverted_index":{"Many":[0],"bioinformatics":[1],"studies":[2],"aim":[3],"to":[4,13,41,74,178],"identify":[5],"markers,":[6],"or":[7,27],"features":[8,45,71],"that":[9,63,154,167],"can":[10],"be":[11,39],"used":[12],"discriminate":[14],"between":[15,30],"distinct":[16],"groups.":[17],"In":[18],"problems":[19],"where":[20,28],"strong":[21],"individual":[22],"markers":[23],"are":[24,33],"not":[25],"available,":[26,94],"interactions":[29],"gene":[31],"products":[32],"of":[34,44,70,114,142,172],"primary":[35],"interest,":[36],"it":[37,106],"may":[38],"necessary":[40],"consider":[42],"combinations":[43],"as":[46],"a":[47,56,65,131],"marker":[48],"family.":[49],"To":[50,123],"this":[51,101,125],"end,":[52],"recent":[53],"work":[54,129],"proposes":[55,130],"hierarchical":[57],"Bayesian":[58],"framework":[59],"for":[60,100],"feature":[61,80,97,151],"selection":[62,98,152],"places":[64],"prior":[66,128],"on":[67,77,157,162],"the":[68,78,95,109,112,140,173,179],"set":[69],"we":[72,146],"wish":[73],"select":[75],"and":[76,120,175],"label-conditioned":[79],"distribution.":[81],"While":[82],"an":[83],"analytical":[84],"posterior":[85,110],"under":[86,181],"Gaussian":[87],"models":[88],"with":[89,136],"block":[90,118,143],"covariance":[91,117],"structures":[92,119],"is":[93],"optimal":[96],"algorithm":[99],"model":[102],"remains":[103],"intractable":[104],"since":[105],"requires":[107],"evaluating":[108],"over":[111],"space":[113,141],"all":[115],"possible":[116],"feature-block":[121],"assignments.":[122],"address":[124],"computational":[126],"barrier,":[127],"simple":[132],"suboptimal":[133],"algorithm,":[134],"2MNC-Robust,":[135],"robust":[137],"performance":[138],"across":[139],"structures.":[144],"Here,":[145],"present":[147],"three":[148],"new":[149],"heuristic":[150],"algorithms":[153],"outperform":[155],"2MNC-Robust":[156],"synthetic":[158],"data.":[159],"Enrichment":[160],"analysis":[161],"real":[163],"cancer":[164],"data":[165],"indicates":[166],"they":[168],"also":[169],"output":[170],"many":[171],"genes":[174],"pathways":[176],"linked":[177],"cancers":[180],"study.":[182]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}