{"id":"https://openalex.org/W7126049133","doi":"https://doi.org/10.1109/bibm66473.2025.11356473","title":"HeteroGraphNet: A Ligand\u2013Receptor Informed, Heterophily-Adapted Graph Neural Network for Cell Type Prediction in scRNA-Seq Data","display_name":"HeteroGraphNet: A Ligand\u2013Receptor Informed, Heterophily-Adapted Graph Neural Network for Cell Type Prediction in scRNA-Seq Data","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126049133","doi":"https://doi.org/10.1109/bibm66473.2025.11356473"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5082697265","display_name":"Mahshad Hashemi","orcid":null},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Mahshad Hashemi","raw_affiliation_strings":["School of Computer Science, University of Windsor,Windsor,Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor,Windsor,Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124211815","display_name":"Sharjeel Mustafa","orcid":null},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sharjeel Mustafa","raw_affiliation_strings":["School of Computer Science, University of Windsor,Windsor,Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor,Windsor,Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068134356","display_name":"Alioune Ngom","orcid":null},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alioune Ngom","raw_affiliation_strings":["School of Computer Science, University of Windsor,Windsor,Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor,Windsor,Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102351961","display_name":"Luis Rueda","orcid":null},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Luis Rueda","raw_affiliation_strings":["School of Computer Science, University of Windsor,Windsor,Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor,Windsor,Canada","institution_ids":["https://openalex.org/I74413500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082697265"],"corresponding_institution_ids":["https://openalex.org/I74413500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67315681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6858","last_page":"6864"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9700999855995178,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9700999855995178,"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":0.010499999858438969,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.006500000134110451,"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/scalability","display_name":"Scalability","score":0.5641999840736389},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4636000096797943},{"id":"https://openalex.org/keywords/biological-data","display_name":"Biological data","score":0.4602999985218048},{"id":"https://openalex.org/keywords/biological-network","display_name":"Biological network","score":0.4551999866962433},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.421999990940094},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40059998631477356},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.3668999969959259},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.36570000648498535},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.3528999984264374}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281000018119812},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5641999840736389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4934999942779541},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4636000096797943},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.4602999985218048},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.4551999866962433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45419999957084656},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44940000772476196},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.3668999969959259},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.36570000648498535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3547999858856201},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.30889999866485596},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2919999957084656},{"id":"https://openalex.org/C55105296","wikidata":"https://www.wikidata.org/wiki/Q841382","display_name":"Interaction network","level":3,"score":0.2793999910354614},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":27,"referenced_works":["https://openalex.org/W1016059894","https://openalex.org/W2069089843","https://openalex.org/W2337340335","https://openalex.org/W2523620612","https://openalex.org/W2794480084","https://openalex.org/W2949177718","https://openalex.org/W2949237386","https://openalex.org/W2990908872","https://openalex.org/W3007935255","https://openalex.org/W3092318937","https://openalex.org/W3138479716","https://openalex.org/W3153881663","https://openalex.org/W3164112499","https://openalex.org/W3164692211","https://openalex.org/W3164766680","https://openalex.org/W3184931457","https://openalex.org/W3210034512","https://openalex.org/W4205126801","https://openalex.org/W4231449374","https://openalex.org/W4249723702","https://openalex.org/W4281716326","https://openalex.org/W4287012481","https://openalex.org/W4313304133","https://openalex.org/W4378212544","https://openalex.org/W4394881579","https://openalex.org/W4404641933","https://openalex.org/W4410309110"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4],"emerged":[5],"as":[6],"powerful":[7],"tools":[8],"for":[9,201],"modeling":[10],"complex":[11],"relational":[12],"data,":[13,39],"yet":[14],"most":[15],"existing":[16],"architectures":[17],"assume":[18],"homophily-where":[19],"connected":[20],"nodes":[21],"share":[22],"similar":[23],"features-an":[24],"assumption":[25],"that":[26,81,119,175],"does":[27],"not":[28],"hold":[29],"in":[30,58,192],"many":[31],"biological":[32,203],"systems.":[33],"In":[34],"single-cell":[35,194],"RNA":[36],"sequencing":[37],"(scRNA-seq)":[38],"intercellular":[40],"communication":[41],"networks":[42],"often":[43],"exhibit":[44],"heterophily,":[45],"with":[46,76,165,179],"meaningful":[47,188],"interactions":[48,87],"occurring":[49],"between":[50],"dissimilar":[51],"cell":[52,139,189],"types.":[53,140],"Moreover,":[54],"conventional":[55],"graph":[56],"construction":[57],"this":[59],"domain":[60],"frequently":[61],"relies":[62],"on":[63,169],"arbitrary":[64],"similarity":[65],"thresholds,":[66],"overlooking":[67],"biologically":[68,96,187],"validated":[69],"interaction":[70,195],"pathways.":[71],"We":[72,125],"address":[73],"these":[74],"limitations":[75],"HeteroGraphNet,":[77],"a":[78,103,148,198],"heterophily-adapted":[79],"GNN":[80],"incorporates":[82],"ligand-receptor":[83],"(<tex":[84],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[85],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{L}-\\mathbf{R}$</tex>)":[86],"inferred":[88],"from":[89],"scRNA-seq":[90,143],"data":[91],"using":[92],"LIANA":[93],"to":[94],"construct":[95],"grounded":[97],"cell-cell":[98],"graphs.":[99,171],"Our":[100],"model":[101],"combines":[102],"bi-kernel":[104],"aggregation":[105],"mechanism-capable":[106],"of":[107],"capturing":[108],"both":[109],"homophilic":[110],"and":[111,159,186],"heterophilic":[112],"signals-with":[113],"cosine":[114],"similarity-guided":[115],"adaptive":[116,180],"random":[117],"walks":[118],"dynamically":[120],"update":[121],"neighborhoods":[122],"during":[123],"training.":[124],"further":[126],"mitigate":[127],"class":[128],"imbalance":[129],"through":[130],"weighted":[131],"loss":[132],"functions,":[133],"ensuring":[134],"robust":[135],"performance":[136],"across":[137],"underrepresented":[138],"Across":[141],"six":[142],"datasets,":[144],"HeteroGraphNet":[145],"consistently":[146],"outperforms":[147],"multi-layer":[149],"perceptron":[150],"(MLP),":[151],"four":[152],"standard":[153],"GNNs":[154,162],"(GCN,":[155],"GAT,":[156],"GraphSAGE,":[157],"MixHop),":[158],"two":[160],"heterophily-specific":[161],"(H2GCN,":[163],"GBK-GNN),":[164],"especially":[166],"strong":[167],"gains":[168],"low-homophily":[170],"These":[172],"results":[173],"demonstrate":[174],"incorporating":[176],"ligand-receptor-informed":[177],"connectivity":[178],"neighborhood":[181],"exploration":[182],"enables":[183],"more":[184],"accurate":[185],"type":[190],"prediction":[191],"heterogeneous":[193],"networks,":[196],"offering":[197],"scalable":[199],"framework":[200],"broader":[202],"network":[204],"analysis.":[205]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}