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RNA velocity predicts transcriptome dynamics, yet cannot be extended to other layers such as the regulome, leaving chromatin accessibility dynamics unresolved.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We developed mmVelo (multimodal velocity of single cells), a deep generative model that infers cell state dynamics from spliced and unspliced mRNA and projects them onto other modalities, yielding chromatin velocity at single-peak resolution. In developing mouse brain, mmVelo accurately recovered accessibility dynamics; in mouse skin, it identified transcription factors regulating accessibility. Decomposing posterior velocity variability into manifold-aligned and off-manifold components revealed modality-specific uncertainty structure, with chromatin fluctuation elevated near lineage branching. Using multiomics data as a bridge, mmVelo inferred the dynamics of missing modalities from single-modal human brain data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Source code is freely available under the MIT license at https:\/\/github.com\/nomuhyooon\/mmVelo; the version and test data used here are archived at https:\/\/doi.org\/10.5281\/zenodo.20103609.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag652","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T04:16:56Z","timestamp":1788236216000},"source":"Crossref","is-referenced-by-count":0,"title":["mmVelo: a deep generative model for estimating cell state-dependent dynamics across multiple modalities"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-4463-754X","authenticated-orcid":false,"given":"Satoshi","family":"Nomura","sequence":"first","affiliation":[{"name":"Japanese Red Cross Aichi Medical Center, Nagoya Daiichi Hospital , Nagoya,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1363-7153","authenticated-orcid":false,"given":"Yasuhiro","family":"Kojima","sequence":"additional","affiliation":[{"name":"Laboratory of Computational Life Science, National Cancer Center Research Institute , Tokyo,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kodai","family":"Minoura","sequence":"additional","affiliation":[{"name":"Japanese Red Cross Aichi Medical Center, Nagoya Daiichi Hospital , Nagoya,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1623-0738","authenticated-orcid":false,"given":"Shuto","family":"Hayashi","sequence":"additional","affiliation":[{"name":"Department of Computational and Systems Biology, Division of Biological Data Science, Medical Research Laboratory, Institute for Integrated Research, Institute of Science Tokyo , Tokyo,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ko","family":"Abe","sequence":"additional","affiliation":[{"name":"Department of Computational and Systems Biology, Division of Biological Data Science, Medical Research Laboratory, Institute for Integrated Research, Institute of Science Tokyo , Tokyo,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haruka","family":"Hirose","sequence":"additional","affiliation":[{"name":"Department of Computational and Systems Biology, Division of Biological Data 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