{"id":"https://openalex.org/W7162094686","doi":"https://doi.org/10.48550/arxiv.2605.21502","title":"Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks","display_name":"Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7162094686","doi":"https://doi.org/10.48550/arxiv.2605.21502"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21502","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21502","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.21502","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135887046","display_name":"Kyle Higgins","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Higgins, Kyle","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050041550","display_name":"Ivan Laponogov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laponogov, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135883245","display_name":"Dennis Veselkov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Veselkov, Dennis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135355734","display_name":"Kirill Veselkov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Veselkov, Kirill","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.8787999749183655,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.8787999749183655,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.045099999755620956,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.012000000104308128,"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/interpretability","display_name":"Interpretability","score":0.9045000076293945},{"id":"https://openalex.org/keywords/biological-network","display_name":"Biological network","score":0.6270999908447266},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4374000132083893},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.41769999265670776},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.3725000023841858},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34860000014305115},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.33889999985694885},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.33309999108314514},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.33250001072883606}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9045000076293945},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.6270999908447266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6018000245094299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44769999384880066},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.428600013256073},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39980000257492065},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36739999055862427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36419999599456787},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.33309999108314514},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C2991772755","wikidata":"https://www.wikidata.org/wiki/Q751748","display_name":"Gene interaction","level":3,"score":0.2924000024795532},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C152662350","wikidata":"https://www.wikidata.org/wiki/Q815297","display_name":"Systems biology","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2809000015258789},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21502","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21502","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.21502","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21502","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4558643102645874,"id":"https://metadata.un.org/sdg/16"},{"display_name":"Reduced inequalities","score":0.40525728464126587,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0],"neural":[1],"networks":[2],"(GNNs)":[3],"are":[4],"increasingly":[5],"used":[6,31],"to":[7],"model":[8],"biological":[9,238],"systems,":[10],"yet":[11],"the":[12,112],"reliability":[13],"of":[14,104,135,187,213,233],"post-hoc":[15],"explanation":[16,70],"methods":[17,71],"for":[18,45,79,126],"recovering":[19],"meaningful":[20],"molecular":[21,243],"mechanisms":[22],"remains":[23],"unclear.":[24],"Here,":[25],"we":[26,67,98,169],"systematically":[27],"evaluate":[28],"four":[29],"widely":[30],"approaches:":[32],"Saliency":[33],"Attribution":[34],"(SA),":[35],"Integrated":[36],"Gradients":[37],"(IG),":[38],"GNNExplainer,":[39],"and":[40,85,91,116,128,130,148,158,223,240],"Layer-wise":[41],"Relevance":[42],"Propagation":[43],"(LRP)":[44],"identifying":[46],"disease-relevant":[47],"structure":[48],"in":[49,107,111],"breast":[50],"cancer":[51,137,189,216],"RNA-seq":[52],"data":[53],"projected":[54],"onto":[55],"a":[56,100,122,142,171,174],"protein-protein":[57],"interaction":[58],"network.":[59],"Using":[60],"synthetic":[61],"benchmarks":[62],"with":[63,132,153,178],"known":[64,136],"ground-truth":[65],"motifs,":[66],"show":[68],"that":[69,230],"recover":[72,88],"distinct":[73],"signal":[74],"organizations:":[75],"SA":[76,159],"performs":[77],"best":[78],"sparse":[80],"single-node":[81],"drivers,":[82],"whereas":[83],"IG":[84,127,154],"LRP":[86,129],"preferentially":[87],"distributed":[89],"pathway-like":[90],"cascade-like":[92],"signals.":[93],"In":[94],"TCGA":[95],"BRCA":[96],"data,":[97],"identify":[99],"consistent":[101],"topological":[102],"signature":[103],"disease-associated":[105],"hubs":[106],"which":[108],"attribution":[109],"peaks":[110],"immediate":[113],"1-hop":[114],"neighborhood":[115],"decays":[117],"across":[118,181],"successive":[119],"network":[120],"shells,":[121],"pattern":[123],"most":[124],"pronounced":[125],"associated":[131],"strong":[133],"enrichment":[134,147,157,208],"hubs.":[138],"We":[139],"further":[140,209],"observe":[141],"trade-off":[143],"between":[144],"local":[145,156],"hub":[146,176],"global":[149,162],"gene":[150],"ranking":[151,180],"performance,":[152],"optimizing":[155],"achieving":[160],"superior":[161],"discrimination.":[163],"Motivated":[164],"by":[165],"these":[166,227],"complementary":[167],"behaviors,":[168],"introduce":[170],"framework":[172],"combining":[173],"shell-based":[175],"score":[177],"consensus":[179],"explainers.":[182],"Consensus":[183],"scores":[184],"improve":[185,237],"prioritization":[186],"canonical":[188],"genes":[190],"(TP53,":[191],"BRCA1,":[192],"ESR1,":[193],"MYC),":[194],"reduce":[195],"dependence":[196],"on":[197],"node":[198],"degree,":[199],"and,":[200],"especially":[201],"when":[202],"tuned,":[203],"outperform":[204],"individual":[205],"methods.":[206],"Pathway":[207],"reveals":[210],"improved":[211],"recovery":[212],"biologically":[214,241],"coherent":[215],"programs,":[217],"including":[218],"ERBB2,":[219],"RTK,":[220],"MAPK,":[221],"immune,":[222],"cytokine":[224],"signaling.":[225],"Together,":[226],"results":[228],"demonstrate":[229],"topology-aware":[231],"integration":[232],"graph":[234],"explanations":[235],"can":[236],"interpretability":[239],"relevant":[242],"recovery.":[244]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-23T00:00:00"}