{"id":"https://openalex.org/W2004039601","doi":"https://doi.org/10.1142/s0219720010004914","title":"ADDITIVE RISK ANALYSIS OF MICROARRAY GENE EXPRESSION DATA VIA CORRELATION PRINCIPAL COMPONENT REGRESSION","display_name":"ADDITIVE RISK ANALYSIS OF MICROARRAY GENE EXPRESSION DATA VIA CORRELATION PRINCIPAL COMPONENT REGRESSION","publication_year":2010,"publication_date":"2010-05-11","ids":{"openalex":"https://openalex.org/W2004039601","doi":"https://doi.org/10.1142/s0219720010004914","mag":"2004039601"},"language":"en","primary_location":{"id":"doi:10.1142/s0219720010004914","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219720010004914","pdf_url":null,"source":{"id":"https://openalex.org/S155349577","display_name":"Journal of Bioinformatics and Computational Biology","issn_l":"0219-7200","issn":["0219-7200","1757-6334"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Bioinformatics and Computational Biology","raw_type":"journal-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/A5048109679","display_name":"Yichuan Zhao","orcid":"https://orcid.org/0000-0002-5069-1968"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"YICHUAN ZHAO","raw_affiliation_strings":["Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA","Department of Mathematics and Statistics , Georgia State University , Atlanta , GA 30303 , USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA","institution_ids":["https://openalex.org/I181565077"]},{"raw_affiliation_string":"Department of Mathematics and Statistics , Georgia State University , Atlanta , GA 30303 , USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040037562","display_name":"GUOSHEN WANG","orcid":null},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"GUOSHEN WANG","raw_affiliation_strings":["Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA","Department of Mathematics and Statistics , Georgia State University , Atlanta , GA 30303 , USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA","institution_ids":["https://openalex.org/I181565077"]},{"raw_affiliation_string":"Department of Mathematics and Statistics , Georgia State University , Atlanta , GA 30303 , USA","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048109679"],"corresponding_institution_ids":["https://openalex.org/I181565077"],"apc_list":null,"apc_paid":null,"fwci":0.793,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70303237,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"08","issue":"04","first_page":"645","last_page":"659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9991000294685364,"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":0.9991000294685364,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9584000110626221,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.6934518814086914},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.6273634433746338},{"id":"https://openalex.org/keywords/censoring","display_name":"Censoring (clinical trials)","score":0.6223008632659912},{"id":"https://openalex.org/keywords/principal-component-regression","display_name":"Principal component regression","score":0.5308452844619751},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5171946287155151},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5039533972740173},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.495364785194397},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4906100332736969},{"id":"https://openalex.org/keywords/microarray-analysis-techniques","display_name":"Microarray analysis techniques","score":0.45797914266586304},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4482571482658386},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.44629770517349243},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.44325515627861023},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4330158531665802},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.43180060386657715},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.42702263593673706},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.42012161016464233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31659168004989624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27080026268959045},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.2190011441707611},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.18850776553153992},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.15613466501235962},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.10818624496459961}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6934518814086914},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.6273634433746338},{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.6223008632659912},{"id":"https://openalex.org/C74887250","wikidata":"https://www.wikidata.org/wiki/Q3455892","display_name":"Principal component regression","level":3,"score":0.5308452844619751},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5171946287155151},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5039533972740173},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.495364785194397},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4906100332736969},{"id":"https://openalex.org/C8415881","wikidata":"https://www.wikidata.org/wiki/Q6839217","display_name":"Microarray analysis techniques","level":4,"score":0.45797914266586304},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4482571482658386},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.44629770517349243},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.44325515627861023},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4330158531665802},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.43180060386657715},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.42702263593673706},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42012161016464233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31659168004989624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27080026268959045},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2190011441707611},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.18850776553153992},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.15613466501235962},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.10818624496459961},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219720010004914","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219720010004914","pdf_url":null,"source":{"id":"https://openalex.org/S155349577","display_name":"Journal of Bioinformatics and Computational Biology","issn_l":"0219-7200","issn":["0219-7200","1757-6334"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Bioinformatics and Computational Biology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320311089","display_name":"National Security Agency","ror":"https://ror.org/0047bvr32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W221489729","https://openalex.org/W1969423031","https://openalex.org/W1969989170","https://openalex.org/W1976564639","https://openalex.org/W1989193879","https://openalex.org/W1989539998","https://openalex.org/W1989979925","https://openalex.org/W2003695698","https://openalex.org/W2018116321","https://openalex.org/W2020414107","https://openalex.org/W2029352098","https://openalex.org/W2052464909","https://openalex.org/W2057527240","https://openalex.org/W2062460807","https://openalex.org/W2063978378","https://openalex.org/W2070496276","https://openalex.org/W2074682976","https://openalex.org/W2104969279","https://openalex.org/W2119021772","https://openalex.org/W2123664981","https://openalex.org/W2123672572","https://openalex.org/W2135046866","https://openalex.org/W2146320559","https://openalex.org/W2147246240","https://openalex.org/W2151105312","https://openalex.org/W2158497151","https://openalex.org/W2163529608","https://openalex.org/W2163563958","https://openalex.org/W2797502950","https://openalex.org/W2955331105","https://openalex.org/W3085323863","https://openalex.org/W3099514962","https://openalex.org/W4205969772","https://openalex.org/W4242768823","https://openalex.org/W4245024447","https://openalex.org/W4250857377"],"related_works":["https://openalex.org/W2985746494","https://openalex.org/W4206042385","https://openalex.org/W2511384863","https://openalex.org/W2080773131","https://openalex.org/W2096089271","https://openalex.org/W2923628599","https://openalex.org/W2014100433","https://openalex.org/W2792777176","https://openalex.org/W2587771768","https://openalex.org/W1967539619"],"abstract_inverted_index":{"In":[0,26,61],"order":[1],"to":[2,20,23,44,72,108,125,133],"predict":[3,115],"future":[4],"patients'":[5],"survival":[6,24,37,77,117],"time":[7],"based":[8],"on":[9,56],"their":[10],"microarray":[11],"gene":[12,50],"expression":[13,51],"data,":[14],"one":[15],"interesting":[16],"question":[17],"is":[18,123,141],"how":[19,110],"relate":[21],"genes":[22],"outcomes.":[25],"this":[27],"paper,":[28],"by":[29,143],"applying":[30],"a":[31,41,46],"semi-parametric":[32,81],"additive":[33,82],"risk":[34,83],"model":[35,84,113,161],"in":[36],"analysis,":[38],"we":[39,65],"propose":[40],"new":[42],"approach":[43,140],"conduct":[45],"careful":[47],"analysis":[48],"of":[49],"data":[52,78,149,154,164],"with":[53,74,86],"the":[54,57,62,67,80,92,96,112,116,120,134,137,144,160,163],"focus":[55],"model's":[58],"predictive":[59],"ability.":[60],"proposed":[63,121,138],"method,":[64],"apply":[66],"correlation":[68],"principal":[69],"component":[70],"regression":[71],"deal":[73],"right":[75],"censoring":[76],"under":[79,95],"frame":[85],"high-dimensional":[87],"covariates.":[88],"We":[89],"also":[90],"employ":[91],"time-dependent":[93],"area":[94],"receiver":[97],"operating":[98],"characteristic":[99],"curve":[100],"and":[101,151],"root":[102],"mean":[103],"squared":[104],"error":[105],"for":[106],"prediction":[107],"assess":[109],"well":[111],"can":[114],"time.":[118],"Furthermore,":[119],"method":[122],"able":[124],"identify":[126],"significant":[127],"genes,":[128],"which":[129],"are":[130],"significantly":[131],"related":[132],"disease.":[135],"Finally,":[136],"useful":[139],"illustrated":[142],"diffuse":[145],"large":[146],"B-cell":[147],"lymphoma":[148],"set":[150],"breast":[152],"cancer":[153],"set.":[155],"The":[156],"results":[157],"show":[158],"that":[159],"fits":[162],"sets":[165],"very":[166],"well.":[167]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}