{"id":"https://openalex.org/W2964304355","doi":"https://doi.org/10.1093/bioinformatics/bty429","title":"A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data","display_name":"A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data","publication_year":2018,"publication_date":"2018-05-23","ids":{"openalex":"https://openalex.org/W2964304355","doi":"https://doi.org/10.1093/bioinformatics/bty429","mag":"2964304355","pmid":"https://pubmed.ncbi.nlm.nih.gov/29850911"},"language":"en","primary_location":{"id":"doi:10.1093/bioinformatics/bty429","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bioinformatics/bty429","pdf_url":null,"source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"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/A5032281061","display_name":"Yunchuan Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunchuan Kong","raw_affiliation_strings":["Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA","Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016835023","display_name":"Tianwei Yu","orcid":"https://orcid.org/0000-0003-2502-1628"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianwei Yu","raw_affiliation_strings":["Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA","Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA","institution_ids":["https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016835023"],"corresponding_institution_ids":["https://openalex.org/I150468666"],"apc_list":{"value":3618,"currency":"USD","value_usd":3618},"apc_paid":null,"fwci":5.1914,"has_fulltext":false,"cited_by_count":120,"citation_normalized_percentile":{"value":0.9681541,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"34","issue":"21","first_page":"3727","last_page":"3737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.3605000078678131,"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":0.3605000078678131,"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":0.149399995803833,"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/T11297","display_name":"Ferroptosis and cancer prognosis","score":0.1379999965429306,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8409433364868164},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7528169751167297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6407251954078674},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6104008555412292},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6083291172981262},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6027454733848572},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5237460136413574},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4791264235973358},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4395429491996765},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.434856653213501},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4100307822227478},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3848128020763397},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09838953614234924}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8409433364868164},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7528169751167297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6407251954078674},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6104008555412292},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6083291172981262},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6027454733848572},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5237460136413574},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4791264235973358},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4395429491996765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.434856653213501},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4100307822227478},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3848128020763397},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09838953614234924},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012313","descriptor_name":"RNA","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012313","descriptor_name":"RNA","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012313","descriptor_name":"RNA","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016678","descriptor_name":"Genome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016678","descriptor_name":"Genome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016678","descriptor_name":"Genome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D053263","descriptor_name":"Gene Regulatory Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D053263","descriptor_name":"Gene Regulatory Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D053263","descriptor_name":"Gene Regulatory Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1093/bioinformatics/bty429","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bioinformatics/bty429","pdf_url":null,"source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},{"id":"pmid:29850911","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29850911","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":"Bioinformatics (Oxford, England)","raw_type":null},{"id":"pmh:oai:europepmc.org:5784972","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6198851","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G3964006637","display_name":null,"funder_award_id":"R01GM124061","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7211878532","display_name":null,"funder_award_id":"R01 GM124061","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W136733156","https://openalex.org/W600208884","https://openalex.org/W810230962","https://openalex.org/W1164040328","https://openalex.org/W1484418241","https://openalex.org/W1488367544","https://openalex.org/W1684305122","https://openalex.org/W1813571362","https://openalex.org/W1892067186","https://openalex.org/W1896601755","https://openalex.org/W1979328769","https://openalex.org/W1987776395","https://openalex.org/W1990792023","https://openalex.org/W2005138964","https://openalex.org/W2008620264","https://openalex.org/W2024311320","https://openalex.org/W2031218556","https://openalex.org/W2032875317","https://openalex.org/W2044702943","https://openalex.org/W2061771504","https://openalex.org/W2080922866","https://openalex.org/W2090463559","https://openalex.org/W2096283457","https://openalex.org/W2097168074","https://openalex.org/W2106100979","https://openalex.org/W2116063398","https://openalex.org/W2117539524","https://openalex.org/W2126797928","https://openalex.org/W2128689695","https://openalex.org/W2130998029","https://openalex.org/W2134887638","https://openalex.org/W2135046866","https://openalex.org/W2138049103","https://openalex.org/W2138255346","https://openalex.org/W2140883620","https://openalex.org/W2146408674","https://openalex.org/W2146899967","https://openalex.org/W2149166498","https://openalex.org/W2153238348","https://openalex.org/W2153601733","https://openalex.org/W2154947819","https://openalex.org/W2157840751","https://openalex.org/W2160514535","https://openalex.org/W2291451258","https://openalex.org/W2308057476","https://openalex.org/W2311607323","https://openalex.org/W2329662673","https://openalex.org/W2335012284","https://openalex.org/W2415153693","https://openalex.org/W2463255141","https://openalex.org/W2486096428","https://openalex.org/W2523377377","https://openalex.org/W2548769923","https://openalex.org/W2557283755","https://openalex.org/W2560367415","https://openalex.org/W2560816154","https://openalex.org/W2590538275","https://openalex.org/W2593086047","https://openalex.org/W2724532648","https://openalex.org/W2744988474","https://openalex.org/W2745190939","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W6658223896","https://openalex.org/W6698064614","https://openalex.org/W6740490807"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3099765033","https://openalex.org/W3155717344","https://openalex.org/W1770458422","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Motivation:":[0],"Gene":[1],"expression":[2],"data":[3,154,217],"represents":[4],"a":[5,52,103,157,164,192],"unique":[6],"challenge":[7],"in":[8],"predictive":[9],"model":[10],"building,":[11],"because":[12,64],"of":[13,17,25,34,69,71,76,83,92,120],"the":[14,22,59,80,84,90,109,123,144,189,196],"small":[15],"number":[16],"samples":[18],"(n)":[19],"compared":[20],"with":[21],"huge":[23],"amount":[24],"features":[26,72,121],"(p).":[27],"This":[28],"'n\u226ap'":[29],"property":[30],"has":[31],"hampered":[32],"application":[33],"deep":[35,124],"learning":[36,43],"techniques":[37],"for":[38],"disease":[39],"outcome":[40],"classification.":[41],"Sparse":[42],"by":[44],"incorporating":[45],"external":[46,117],"gene":[47,85],"network":[48,86,126,137],"information":[49,119],"could":[50],"be":[51],"potential":[53],"solution":[54],"to":[55,89,115,132,139,195],"this":[56],"issue.":[57],"Still,":[58],"problem":[60],"is":[61,87,130,191,210],"very":[62],"challenging":[63],"(i)":[65],"there":[66],"are":[67,218],"tens":[68],"thousands":[70],"and":[73,101,152,163,182,201,206],"only":[74],"hundreds":[75],"training":[77],"samples,":[78],"(ii)":[79],"scale-free":[81],"structure":[82],"unfriendly":[88],"setup":[91],"convolutional":[93],"neural":[94,125],"networks.":[95],"Results:":[96],"To":[97,142],"address":[98],"these":[99],"issues":[100],"build":[102],"robust":[104],"classification":[105,180,199],"model,":[106],"we":[107,147],"propose":[108],"Graph-Embedded":[110],"Deep":[111],"Feedforward":[112],"Networks":[113],"(GEDFN),":[114],"integrate":[116],"relational":[118],"into":[122],"architecture.":[127],"The":[128,173,177,208],"method":[129,190,209],"able":[131],"achieve":[133],"sparse":[134],"connection":[135],"between":[136],"layers":[138],"prevent":[140],"overfitting.":[141],"validate":[143],"method's":[145],"capability,":[146],"conducted":[148],"both":[149],"simulation":[150],"experiments":[151],"real":[153],"analysis":[155],"using":[156],"breast":[158],"invasive":[159],"carcinoma":[160,169],"RNA-seq":[161,170],"dataset":[162,171],"kidney":[165],"renal":[166],"clear":[167],"cell":[168],"from":[172],"Cancer":[174],"Genome":[175],"Atlas.":[176],"resulting":[178],"high":[179],"accuracy":[181],"easily":[183],"interpretable":[184],"feature":[185,202],"selection":[186,203],"results":[187],"suggest":[188],"useful":[193],"addition":[194],"current":[197],"graph-guided":[198],"models":[200],"procedures.":[204],"Availability":[205],"implementation:":[207],"available":[211,219],"at":[212,220],"https://github.com/yunchuankong/GEDFN.":[213],"Supplementary":[214,216],"information:":[215],"Bioinformatics":[221],"online.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-26T07:53:14.480251","created_date":"2025-10-10T00:00:00"}
