{"id":"https://openalex.org/W7157269160","doi":"https://doi.org/10.48550/arxiv.2604.24371","title":"PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction","display_name":"PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7157269160","doi":"https://doi.org/10.48550/arxiv.2604.24371"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.24371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24371","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.24371","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134766847","display_name":"Di Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Di","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134757434","display_name":"Chupei Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Chupei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111348192","display_name":"Junxiao Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Junxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124973001","display_name":"Jixiu Zhai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhai, Jixiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134811588","display_name":"Moyu Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Moyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5027108468","display_name":"Tianchi Lu","orcid":"https://orcid.org/0000-0001-6111-2020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Tianchi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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/T11297","display_name":"Ferroptosis and cancer prognosis","score":0.42719998955726624,"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"}},"topics":[{"id":"https://openalex.org/T11297","display_name":"Ferroptosis and cancer prognosis","score":0.42719998955726624,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.38670000433921814,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.034299999475479126,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/modular-design","display_name":"Modular design","score":0.7009000182151794},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5496000051498413},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5263000130653381},{"id":"https://openalex.org/keywords/modular-neural-network","display_name":"Modular neural network","score":0.3790000081062317},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.3560999929904938}],"concepts":[{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.7009000182151794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323999762535095},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5496000051498413},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4490000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40119999647140503},{"id":"https://openalex.org/C2781121602","wikidata":"https://www.wikidata.org/wiki/Q3504403","display_name":"Modular neural network","level":4,"score":0.3790000081062317},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3560999929904938},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31610000133514404},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.26339998841285706},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.24371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24371","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.24371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24371","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Cancer":[0],"survival":[1,32,93],"prediction":[2],"from":[3],"multi-omics":[4,31],"data":[5],"remains":[6],"challenging":[7],"because":[8],"prognostic":[9],"signals":[10,71],"are":[11],"high-dimensional,":[12],"heterogeneous,":[13],"and":[14,19,59,62,72,87,101,107],"distributed":[15],"across":[16,82],"interacting":[17],"genes":[18],"pathways.":[20],"We":[21,76],"propose":[22],"PathMoG,":[23],"a":[24,44],"pathway-centric":[25],"modular":[26],"graph":[27],"neural":[28],"network":[29],"for":[30],"prediction.":[33],"PathMoG":[34,78],"reorganizes":[35],"genome-scale":[36],"inputs":[37],"into":[38],"354":[39],"KEGG-informed":[40],"pathway":[41],"modules,":[42],"introduces":[43],"Hierarchical":[45],"Omics":[46],"Modulation":[47],"module":[48],"to":[49,66],"condition":[50],"gene-expression":[51],"representations":[52],"on":[53,79],"mutation,":[54],"copy":[55],"number":[56],"variation,":[57],"pathway,":[58],"clinical":[60,74],"context,":[61],"uses":[63],"dual-level":[64],"attention":[65],"capture":[67],"both":[68],"intra-pathway":[69],"driver":[70],"inter-pathway":[73],"relevance.":[75],"evaluated":[77],"5,650":[80],"patients":[81],"10":[83],"TCGA":[84],"cancer":[85],"types":[86],"observed":[88],"consistent":[89],"improvements":[90],"over":[91],"representative":[92],"baselines.":[94],"The":[95],"framework":[96],"further":[97],"provides":[98],"gene-level,":[99],"pathway-level,":[100],"patient-level":[102],"interpretability,":[103],"supporting":[104],"biologically":[105],"grounded":[106],"clinically":[108],"relevant":[109],"risk":[110],"stratification.":[111]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-29T00:00:00"}
