{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jagtap S"],"funding":["ANR (French National Research Agency)","ANR"],"pagination":["429"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9575224"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(1)"],"pubmed_abstract":["<h4>Background</h4>Gene expression is regulated at different molecular levels, including chromatin accessibility, transcription, RNA maturation, and transport. These regulatory mechanisms have strong connections with cellular metabolism. In order to study the cellular system and its functioning, omics data at each molecular level can be generated and efficiently integrated. Here, we propose BRANENET, a novel multi-omics integration framework for multilayer heterogeneous networks. BRANENET is an expressive, scalable, and versatile method to learn node embeddings, leveraging random walk information within a matrix factorization framework. Our goal is to efficiently integrate multi-omics data to study different regulatory aspects of multilayered processes that occur in organisms. We evaluate "],"journal":["BMC bioinformatics"],"pubmed_title":["BRANEnet: embedding multilayer networks for omics data integration."],"pmcid":["PMC9575224"],"funding_grant_id":["JCJC project GraphIA (ANR-20-CE23-0009-01)"],"pubmed_authors":["Jagtap S","Bidard F","Malliaros FD","Duval L","Pirayre A"],"additional_accession":[]},"is_claimable":false,"name":"BRANEnet: embedding multilayer networks for omics data integration.","description":"<h4>Background</h4>Gene expression is regulated at different molecular levels, including chromatin accessibility, transcription, RNA maturation, and transport. These regulatory mechanisms have strong connections with cellular metabolism. In order to study the cellular system and its functioning, omics data at each molecular level can be generated and efficiently integrated. Here, we propose BRANENET, a novel multi-omics integration framework for multilayer heterogeneous networks. BRANENET is an expressive, scalable, and versatile method to learn node embeddings, leveraging random walk information within a matrix factorization framework. Our goal is to efficiently integrate multi-omics data to study different regulatory aspects of multilayered processes that occur in organisms. We evaluate ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Oct","modification":"2025-04-18T22:53:17.04Z","creation":"2025-02-19T01:56:13.247Z"},"accession":"S-EPMC9575224","cross_references":{"pubmed":["36245002"],"doi":["10.1186/s12859-022-04955-w"]}}