{"id":"https://openalex.org/W2039659044","doi":"https://doi.org/10.1109/bibmw.2011.6112460","title":"Gene-gene interaction analysis for the survival phenotype based on the standardized residuals from parametric regression models","display_name":"Gene-gene interaction analysis for the survival phenotype based on the standardized residuals from parametric regression models","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2039659044","doi":"https://doi.org/10.1109/bibmw.2011.6112460","mag":"2039659044"},"language":"en","primary_location":{"id":"doi:10.1109/bibmw.2011.6112460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibmw.2011.6112460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","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/A5034909134","display_name":"Seungyeoun Lee","orcid":"https://orcid.org/0000-0001-7941-8933"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungyeoun Lee","raw_affiliation_strings":["Department of Mathematics and Statistics, Sejong University, South Korea","Department of Mathematics and Statistics, Sejong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Sejong University, South Korea","institution_ids":["https://openalex.org/I28777354"]},{"raw_affiliation_string":"Department of Mathematics and Statistics, Sejong University","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025525869","display_name":"Jinseok Oh","orcid":null},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinseok Oh","raw_affiliation_strings":["Department of Mathematics and Statistics, Sejong University, South Korea","Department of Mathematics and Statistics, Sejong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Sejong University, South Korea","institution_ids":["https://openalex.org/I28777354"]},{"raw_affiliation_string":"Department of Mathematics and Statistics, Sejong University","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025860059","display_name":"Minseok Kwon","orcid":"https://orcid.org/0000-0001-6938-8048"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Min-Seok Kwon","raw_affiliation_strings":["Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea","Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-747, #N#Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-747, #N#Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108621611","display_name":"Taesung Park","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taesung Park","raw_affiliation_strings":["Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea","Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-747, #N#Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-747, #N#Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.10651105,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"31","issue":null,"first_page":"725","last_page":"729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10261","display_name":"Genetic Associations and Epidemiology","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/T10261","display_name":"Genetic Associations and Epidemiology","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/T10885","display_name":"Gene expression and cancer classification","score":0.9926999807357788,"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":0.9912999868392944,"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/multifactor-dimensionality-reduction","display_name":"Multifactor dimensionality reduction","score":0.9120011925697327},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.7454522848129272},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.6510307788848877},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5168964862823486},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4578931927680969},{"id":"https://openalex.org/keywords/log-rank-test","display_name":"Log-rank test","score":0.4475463628768921},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.44389185309410095},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.437706857919693},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.43040335178375244},{"id":"https://openalex.org/keywords/genome-wide-association-study","display_name":"Genome-wide association study","score":0.43040335178375244},{"id":"https://openalex.org/keywords/single-nucleotide-polymorphism","display_name":"Single-nucleotide polymorphism","score":0.42285093665122986},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3731054961681366},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.3288002610206604},{"id":"https://openalex.org/keywords/genotype","display_name":"Genotype","score":0.31586766242980957},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.28928977251052856},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.2792236804962158},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2375434935092926},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.19641360640525818},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17645692825317383},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10998174548149109}],"concepts":[{"id":"https://openalex.org/C25249476","wikidata":"https://www.wikidata.org/wiki/Q6934678","display_name":"Multifactor dimensionality reduction","level":5,"score":0.9120011925697327},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7454522848129272},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.6510307788848877},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5168964862823486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4578931927680969},{"id":"https://openalex.org/C66339696","wikidata":"https://www.wikidata.org/wiki/Q6089397","display_name":"Log-rank test","level":3,"score":0.4475463628768921},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.44389185309410095},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.437706857919693},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.43040335178375244},{"id":"https://openalex.org/C106208931","wikidata":"https://www.wikidata.org/wiki/Q1098876","display_name":"Genome-wide association study","level":5,"score":0.43040335178375244},{"id":"https://openalex.org/C153209595","wikidata":"https://www.wikidata.org/wiki/Q501128","display_name":"Single-nucleotide polymorphism","level":4,"score":0.42285093665122986},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3731054961681366},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.3288002610206604},{"id":"https://openalex.org/C135763542","wikidata":"https://www.wikidata.org/wiki/Q106016","display_name":"Genotype","level":3,"score":0.31586766242980957},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.28928977251052856},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.2792236804962158},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2375434935092926},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.19641360640525818},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17645692825317383},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10998174548149109}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibmw.2011.6112460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibmw.2011.6112460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1976634586","https://openalex.org/W2016645182","https://openalex.org/W2063384143","https://openalex.org/W2079861715","https://openalex.org/W2084150578","https://openalex.org/W2154572047"],"related_works":["https://openalex.org/W2109650667","https://openalex.org/W2083447308","https://openalex.org/W3015225818","https://openalex.org/W4308165859","https://openalex.org/W2155829550","https://openalex.org/W3127763960","https://openalex.org/W2147995538","https://openalex.org/W2124303036","https://openalex.org/W2163947145","https://openalex.org/W2147486414"],"abstract_inverted_index":{"Most":[0],"of":[1,33,126,152,181,203,233,267,284],"statistical":[2],"methods":[3,275],"in":[4,28,41,161,254,295,338],"genome-wide":[5],"association":[6],"studies":[7],"(GWAS)":[8],"have":[9,309,328],"been":[10],"developed":[11],"to":[12,37,118,129,137,157,177,184,206,219,243],"identify":[13],"SNP-SNP":[14],"interactions":[15,59,105,194],"using":[16],"a":[17,51,89,108,131,135,182,208,212,217,240],"binary":[18],"phenotype":[19,40,316,334],"for":[20,56,88,102,191],"case-control":[21],"studies.":[22,44],"However,":[23,77],"there":[24],"is":[25,128,205,261],"an":[26,97],"interest":[27],"identifying":[29,192],"SNPs":[30,34],"and":[31,84,143,154,165,225],"combinations":[32],"that":[35,266,273,307,325],"relate":[36],"the":[38,66,74,78,119,150,162,179,185,197,231,234,251,282,288,293,300,305,310,314,323,332,339],"survival":[39,62,120,198,315,333],"many":[42],"cancer":[43],"Recently,":[45],"Gui":[46,268],"et":[47,93,269],"al.":[48,94,270],"(2011)":[49,95],"proposed":[50,96],"novel":[52],"method,":[53],"called":[54,100,189],"Surv-MDR,":[55],"detecting":[57,103,255],"gene-gene":[58,104,193],"associated":[60,195],"with":[61,196,246,286],"time":[63,121],"by":[64,111],"modifying":[65],"multifactor":[67,114],"dimensionality":[68,115],"reduction":[69,116],"(MDR)":[70],"method":[71,80,253],"based":[72,106],"on":[73,107,313,331],"log-rank":[75],"test.":[76],"Surv-MDR":[79,252],"needs":[81],"more-intensive":[82],"computations":[83],"does":[85],"not":[86,327],"allow":[87],"covariate":[90],"adjustment.":[91],"Lee":[92],"alternative":[98],"approach,":[99],"Cox-MDR,":[101],"Cox":[109,163],"model":[110,164,215],"extending":[112],"generalized":[113],"(GMDR)":[117],"phenotype.":[122,199],"The":[123,200,258],"main":[124,201],"idea":[125,180,202],"Cox-MDR":[127,147,183,247],"use":[130,207],"martingale":[132],"residual":[133,210],"as":[134,141,216,223,248,250,263,265,318,336],"score":[136,218],"classify":[138,220],"multi-level":[139,221],"genotypes":[140,222],"high":[142,224],"low":[144,226],"risk":[145,227],"groups.":[146],"also":[148],"allows":[149],"effects":[151],"discrete":[153],"quantitative":[155],"covariates":[156,289,294,306,324],"be":[158],"easily":[159],"adjusted":[160,304,322],"requires":[166],"much":[167],"less":[168],"computation":[169],"than":[170],"Surv-MDR.":[171],"In":[172,278,299],"this":[173],"paper,":[174],"we":[175,280,303,321],"propose":[176],"extend":[178],"parametric":[186,213],"regression":[187,214],"model,":[188],"PRM-MDR":[190,204,245,285],"standardized":[209],"from":[211],"groups":[228],"while":[229,320],"keeping":[230],"rest":[232],"MDR":[235],"procedure":[236],"unchanged.":[237],"We":[238],"performed":[239],"simulation":[241,259],"study":[242],"compare":[244],"well":[249],"two-way":[256],"interactions.":[257],"setting":[260],"constructed":[262],"similar":[264],"(2011),":[271],"so":[272],"three":[274],"are":[276],"comparable.":[277],"addition,":[279],"compared":[281],"power":[283],"adjusting":[287,292],"versus":[290],"without":[291],"two":[296],"different":[297],"scenarios.":[298],"first":[301],"scenario,":[302],"potentially":[308],"significant":[311],"effect":[312,330],"such":[317,335],"age":[319],"might":[326],"any":[329],"sex":[337],"second":[340],"scenario.":[341]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
