{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T07:40:38Z","timestamp":1765438838871,"version":"3.37.3"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"24","license":[{"start":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T00:00:00Z","timestamp":1667347200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100001665","name":"ANR","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001665","name":"French National Research Agency","doi-asserted-by":"publisher","award":["ANR-20-CE23-0009-01"],"award-info":[{"award-number":["ANR-20-CE23-0009-01"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,13]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>The cellular system of a living organism is composed of interacting bio-molecules that control cellular processes at multiple levels. Their correspondences are represented by tightly regulated molecular networks. The increase of omics technologies has favored the generation of large-scale disparate data and the consequent demand for simultaneously using molecular and functional interaction networks: gene co-expression, protein\u2013protein interaction (PPI), genetic interaction and metabolic networks. They are rich sources of information at different molecular levels, and their effective integration is essential to understand cell functioning and their building blocks (proteins). Therefore, it is necessary to obtain informative representations of proteins and their proximity, that are not fully captured by features extracted directly from a single informational level. We propose BraneMF, a novel random walk-based matrix factorization method for learning node representation in a multilayer network, with application to omics data integration.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We test BraneMF with PPI networks of Saccharomyces cerevisiae, a well-studied yeast model organism. We demonstrate the applicability of the learned features for essential multi-omics inference tasks: clustering, function and PPI prediction. We compare it to the state-of-the-art integration methods for multilayer networks. BraneMF outperforms baseline methods by achieving high prediction scores for a variety of downstream tasks. The robustness of results is assessed by an extensive parameter sensitivity analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>BraneMF\u2019s code is freely available at: https:\/\/github.com\/Surabhivj\/BraneMF, along with datasets, embeddings and result files.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac691","type":"journal-article","created":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T13:34:04Z","timestamp":1667309644000},"page":"5383-5389","source":"Crossref","is-referenced-by-count":3,"title":["BraneMF: integration of biological networks for functional analysis of proteins"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7599-5434","authenticated-orcid":false,"given":"Surabhi","family":"Jagtap","sequence":"first","affiliation":[{"name":"IFP Energies Nouvelles , 92852 Rueil-Malmaison, France"},{"name":"Universit\u00e9 Paris-Saclay, CentraleSup\u00e9lec, Inria, Centre for Visual Computing , 91190 Gif-Sur-Yvette, France"}]},{"given":"Abdulkadir","family":"\u00c7elikkanat","sequence":"additional","affiliation":[{"name":"Technical University of Denmark, DTU Compute , 2800 Kongens Lyngby, Denmark"}]},{"given":"Aur\u00e9lie","family":"Pirayre","sequence":"additional","affiliation":[{"name":"IFP Energies Nouvelles , 92852 Rueil-Malmaison, France"}]},{"given":"Fr\u00e9d\u00e9rique","family":"Bidard","sequence":"additional","affiliation":[{"name":"IFP Energies Nouvelles , 92852 Rueil-Malmaison, France"}]},{"given":"Laurent","family":"Duval","sequence":"additional","affiliation":[{"name":"IFP Energies Nouvelles , 92852 Rueil-Malmaison, France"}]},{"given":"Fragkiskos D","family":"Malliaros","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, CentraleSup\u00e9lec, Inria, Centre for Visual Computing , 91190 Gif-Sur-Yvette, France"}]}],"member":"286","published-online":{"date-parts":[[2022,11,2]]},"reference":[{"first-page":"1027","year":"2007","author":"Arthur","key":"2022121418412078900_btac691-B1"},{"key":"2022121418412078900_btac691-B2","first-page":"119","volume-title":"Proceedings of the International Conference Complex Network Application,","author":"Bagavathi","year":"2018"},{"key":"2022121418412078900_btac691-B3","first-page":"3357","article-title":"Exponential family graph embeddings","author":"\u00c7elikkanat","year":"2020","journal-title":"Proc. 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