{"id":"https://openalex.org/W4401242722","doi":"https://doi.org/10.3390/make6030089","title":"Enhanced Graph Representation Convolution: Effective Inferring Gene Regulatory Network Using Graph Convolution Network with Self-Attention Graph Pooling Layer","display_name":"Enhanced Graph Representation Convolution: Effective Inferring Gene Regulatory Network Using Graph Convolution Network with Self-Attention Graph Pooling Layer","publication_year":2024,"publication_date":"2024-08-01","ids":{"openalex":"https://openalex.org/W4401242722","doi":"https://doi.org/10.3390/make6030089"},"language":"en","primary_location":{"id":"doi:10.3390/make6030089","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6030089","pdf_url":"https://www.mdpi.com/2504-4990/6/3/89/pdf?version=1722503404","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/6/3/89/pdf?version=1722503404","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006245202","display_name":"Duaa Mohammad Alawad","orcid":"https://orcid.org/0009-0000-8115-4156"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Duaa Mohammad Alawad","raw_affiliation_strings":["Computer Science, University of New Orleans, 2000 Lakeshore Drive, Math 308, New Orleans, LA 70148, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, University of New Orleans, 2000 Lakeshore Drive, Math 308, New Orleans, LA 70148, USA","institution_ids":["https://openalex.org/I192396691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003710687","display_name":"Ataur Katebi","orcid":"https://orcid.org/0000-0001-8656-5181"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]},{"id":"https://openalex.org/I4210145836","display_name":"Center for Theoretical Biological Physics","ror":"https://ror.org/04hfg7v94","country_code":"US","type":"facility","lineage":["https://openalex.org/I12912129","https://openalex.org/I181547552","https://openalex.org/I2801539370","https://openalex.org/I4210145836","https://openalex.org/I44461941","https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ataur Katebi","raw_affiliation_strings":["Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA","Department of Bioengineering, Northeastern University, Boston, MA 02115, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA","institution_ids":["https://openalex.org/I4210145836","https://openalex.org/I12912129"]},{"raw_affiliation_string":"Department of Bioengineering, Northeastern University, Boston, MA 02115, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055092646","display_name":"Md Tamjidul Hoque","orcid":"https://orcid.org/0000-0002-0110-2194"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Md Tamjidul Hoque","raw_affiliation_strings":["Computer Science, University of New Orleans, 2000 Lakeshore Drive, Math 308, New Orleans, LA 70148, USA"],"raw_orcid":"https://orcid.org/0000-0002-0110-2194","affiliations":[{"raw_affiliation_string":"Computer Science, University of New Orleans, 2000 Lakeshore Drive, Math 308, New Orleans, LA 70148, USA","institution_ids":["https://openalex.org/I192396691"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055092646"],"corresponding_institution_ids":["https://openalex.org/I192396691"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.8739,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73016521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"6","issue":"3","first_page":"1818","last_page":"1839"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9995999932289124,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9995999932289124,"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":0.9994999766349792,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9976000189781189,"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/pooling","display_name":"Pooling","score":0.7188012599945068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6208335757255554},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.6200382709503174},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6160117983818054},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5165737867355347},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.44007232785224915},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.3625686466693878},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34011462330818176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31628739833831787},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.2803313434123993},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.27746760845184326},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.21107706427574158},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.19246312975883484}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7188012599945068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208335757255554},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.6200382709503174},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6160117983818054},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5165737867355347},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44007232785224915},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.3625686466693878},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34011462330818176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31628739833831787},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.2803313434123993},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.27746760845184326},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.21107706427574158},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.19246312975883484}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make6030089","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6030089","pdf_url":"https://www.mdpi.com/2504-4990/6/3/89/pdf?version=1722503404","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:27865070abf94a3c8675d7d1e78f8c48","is_oa":true,"landing_page_url":"https://doaj.org/article/27865070abf94a3c8675d7d1e78f8c48","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 1818-1839 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make6030089","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6030089","pdf_url":"https://www.mdpi.com/2504-4990/6/3/89/pdf?version=1722503404","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401242722.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1976526581","https://openalex.org/W2076513103","https://openalex.org/W2106555403","https://openalex.org/W2109384743","https://openalex.org/W2121695897","https://openalex.org/W2122718339","https://openalex.org/W2133091666","https://openalex.org/W2146756876","https://openalex.org/W2160095931","https://openalex.org/W2163296115","https://openalex.org/W2165073978","https://openalex.org/W2332016763","https://openalex.org/W2548377017","https://openalex.org/W2561175740","https://openalex.org/W2561884319","https://openalex.org/W2583157215","https://openalex.org/W2611864304","https://openalex.org/W2757234574","https://openalex.org/W2775083070","https://openalex.org/W2811124557","https://openalex.org/W2850647469","https://openalex.org/W2887853521","https://openalex.org/W2901292166","https://openalex.org/W2902990089","https://openalex.org/W2936460186","https://openalex.org/W2965570621","https://openalex.org/W2966445777","https://openalex.org/W2985331920","https://openalex.org/W2997831639","https://openalex.org/W2997997679","https://openalex.org/W3034065136","https://openalex.org/W3040672684","https://openalex.org/W3094309150","https://openalex.org/W3095716988","https://openalex.org/W3152893301","https://openalex.org/W3206568895","https://openalex.org/W4200281533","https://openalex.org/W4206804332","https://openalex.org/W4281559042","https://openalex.org/W4362605796","https://openalex.org/W4366726969","https://openalex.org/W4390970134","https://openalex.org/W6679868779","https://openalex.org/W6702046917","https://openalex.org/W6761665040","https://openalex.org/W6765510503","https://openalex.org/W6784741312"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2950199998","https://openalex.org/W2560421304","https://openalex.org/W2951387065","https://openalex.org/W3015684221","https://openalex.org/W4385727351","https://openalex.org/W4306798985","https://openalex.org/W4385417763"],"abstract_inverted_index":{"Studying":[0],"gene":[1,39,143,166,196],"regulatory":[2],"networks":[3],"(GRNs)":[4],"is":[5,99,210],"paramount":[6],"for":[7],"unraveling":[8],"the":[9,34,46,56,97,102,216,232,238,254,272,293,301],"complexities":[10],"of":[11,36,109,142,208,224,229,245,250,262,267,274,286,300],"biological":[12,303],"processes":[13,304],"and":[14,22,62,126,152,163,199,226,247,264,305,311],"their":[15,127,172,306],"associated":[16],"disorders,":[17],"such":[18],"as":[19,91],"diabetes,":[20],"cancer,":[21],"Alzheimer\u2019s":[23],"disease.":[24,312],"Recent":[25],"advancements":[26],"in":[27,53,239,276,292,308],"computational":[28],"biology":[29],"have":[30],"aimed":[31],"to":[32,100,129,135,203,296],"enhance":[33,136],"inference":[35],"GRNs":[37,279],"from":[38,195],"expression":[40,197],"data,":[41],"a":[42,72,92,139,160,180,289],"non-trivial":[43],"task":[44,98],"given":[45],"networks\u2019":[47],"intricate":[48,302],"nature.":[49],"The":[50,206,283],"challenge":[51],"lies":[52],"accurately":[54,277],"identifying":[55],"myriad":[57],"interactions":[58,170],"among":[59,171],"transcription":[60,124,161],"factors":[61,125],"target":[63,165],"genes,":[64],"which":[65,86],"govern":[66],"cellular":[67],"functions.":[68],"This":[69],"research":[70],"introduces":[71],"cutting-edge":[73],"technique,":[74],"EGRC":[75,183,209,220,258,275,287],"(Effective":[76],"GRN":[77,89],"Inference":[78],"applying":[79],"Graph":[80,84],"Convolution":[81],"with":[82],"Self-Attention":[83],"Pooling),":[85],"innovatively":[87],"conceptualizes":[88],"reconstruction":[90],"graph":[93,186,200],"classification":[94],"problem,":[95],"where":[96,159],"discern":[101],"links":[103],"within":[104],"subgraphs":[105,118,149,156],"that":[106,119,191],"encapsulate":[107],"pairs":[108,178],"nodes.":[110],"By":[111],"leveraging":[112],"Spearman\u2019s":[113],"correlation,":[114],"we":[115],"generate":[116],"potential":[117],"bring":[120],"nonlinear":[121],"associations":[122],"between":[123],"targets":[128],"light.":[130],"We":[131],"use":[132],"mutual":[133],"information":[134],"this,":[137],"capturing":[138],"broader":[140],"spectrum":[141],"interactions.":[144],"Our":[145],"methodology":[146],"bifurcates":[147],"these":[148],"into":[150],"\u2018Positive\u2019":[151,155],"\u2018Negative\u2019":[153,174],"categories.":[154],"are":[157,167],"those":[158],"factor":[162],"its":[164],"connected,":[168],"including":[169],"neighbors.":[173],"subgraphs,":[175],"conversely,":[176],"denote":[177],"without":[179],"direct":[181],"connection.":[182],"utilizes":[184],"dual":[185],"convolution":[187],"network":[188],"(GCN)":[189],"models":[190],"exploit":[192],"node":[193],"attributes":[194],"profiles":[198],"embedding":[201],"techniques":[202],"classify":[204],"these.":[205],"performance":[207,285],"substantiated":[211],"by":[212],"comprehensive":[213],"evaluations":[214],"using":[215],"DREAM5":[217],"datasets.":[218],"Notably,":[219],"attained":[221],"an":[222,227,243,248,260,265],"AUROC":[223,244,261],"0.856":[225],"AUPR":[228,249,266],"0.841":[230],"on":[231,253],"E.":[233],"coli":[234],"dataset.":[235],"In":[236],"contrast,":[237],"silico":[240],"dataset":[241],"achieved":[242],"0.5058":[246],"0.958.":[251],"Furthermore,":[252],"S.":[255],"cerevisiae":[256],"dataset,":[257],"recorded":[259],"0.823":[263],"0.822.":[268],"These":[269],"results":[270],"underscore":[271],"robustness":[273],"inferring":[278],"across":[280],"various":[281],"organisms.":[282],"advanced":[284],"represents":[288],"substantial":[290],"advancement":[291],"field,":[294],"promising":[295],"deepen":[297],"our":[298],"comprehension":[299],"implications":[307],"both":[309],"health":[310]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}