{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T19:05:16Z","timestamp":1773515116549,"version":"3.50.1"},"reference-count":72,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,3,9]],"date-time":"2024-03-09T00:00:00Z","timestamp":1709942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,2]]},"abstract":"<jats:title\/>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMuS in terms of transcription factor (TF) targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>HuMMuS is available at https:\/\/github.com\/cantinilab\/HuMMuS.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae143","type":"journal-article","created":{"date-parts":[[2024,3,9]],"date-time":"2024-03-09T17:11:31Z","timestamp":1710004291000},"source":"Crossref","is-referenced-by-count":7,"title":["Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS"],"prefix":"10.1093","volume":"40","author":[{"given":"Remi","family":"Trimbour","sequence":"first","affiliation":[{"name":"Institut Pasteur, Universit\u00e9 Paris Cit\u00e9, CNRS UMR 3738, Machine Learning for Integrative Genomics Group , F-75015 Paris, France"},{"name":"Institut de Biologie de l\u2019Ecole Normale Sup\u00e9rieure, CNRS, INSERM, Ecole Normale Sup\u00e9rieure, Universit\u00e9 PSL , 75005 Paris, France"}]},{"given":"Ina Maria","family":"Deutschmann","sequence":"additional","affiliation":[{"name":"Institut de Biologie de l\u2019Ecole Normale Sup\u00e9rieure, CNRS, INSERM, Ecole Normale Sup\u00e9rieure, Universit\u00e9 PSL , 75005 Paris, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6360-4440","authenticated-orcid":false,"given":"Laura","family":"Cantini","sequence":"additional","affiliation":[{"name":"Institut Pasteur, Universit\u00e9 Paris Cit\u00e9, CNRS UMR 3738, Machine Learning for Integrative Genomics Group , F-75015 Paris, France"},{"name":"Institut de Biologie de l\u2019Ecole Normale Sup\u00e9rieure, CNRS, INSERM, Ecole Normale Sup\u00e9rieure, Universit\u00e9 PSL , 75005 Paris, 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