000299517 001__ 299517
000299517 005__ 20250410152436.0
000299517 0247_ $$2doi$$a10.1038/s41592-025-02608-3
000299517 0247_ $$2pmid$$apmid:40032996
000299517 0247_ $$2ISSN$$a1548-7091
000299517 0247_ $$2ISSN$$a1548-7105
000299517 0247_ $$2altmetric$$aaltmetric:174823497
000299517 037__ $$aDKFZ-2025-00475
000299517 041__ $$aEnglish
000299517 082__ $$a610
000299517 1001_ $$aAivazidis, Alexander$$b0
000299517 245__ $$aCell2fate infers RNA velocity modules to improve cell fate prediction.
000299517 260__ $$aLondon [u.a.]$$bNature Publishing Group$$c2025
000299517 3367_ $$2DRIVER$$aarticle
000299517 3367_ $$2DataCite$$aOutput Types/Journal article
000299517 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1744291441_33
000299517 3367_ $$2BibTeX$$aARTICLE
000299517 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000299517 3367_ $$00$$2EndNote$$aJournal Article
000299517 500__ $$a2025 Apr;22(4):698-707
000299517 520__ $$aRNA velocity exploits the temporal information contained in spliced and unspliced RNA counts to infer transcriptional dynamics. Existing velocity models often rely on coarse biophysical simplifications or numerical approximations to solve the underlying ordinary differential equations (ODEs), which can compromise accuracy in challenging settings, such as complex or weak transcription rate changes across cellular trajectories. Here we present cell2fate, a formulation of RNA velocity based on a linearization of the velocity ODE, which allows solving a biophysically more accurate model in a fully Bayesian fashion. As a result, cell2fate decomposes the RNA velocity solutions into modules, providing a biophysical connection between RNA velocity and statistical dimensionality reduction. We comprehensively benchmark cell2fate in real-world settings, demonstrating enhanced interpretability and power to reconstruct complex dynamics and weak dynamical signals in rare and mature cell types. Finally, we apply cell2fate to the developing human brain, where we spatially map RNA velocity modules onto the tissue architecture, connecting the spatial organization of tissues with temporal dynamics of transcription.
000299517 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0
000299517 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000299517 7001_ $$00000-0002-3685-1988$$aMemi, Fani$$b1
000299517 7001_ $$00000-0001-9110-7441$$aKleshchevnikov, Vitalii$$b2
000299517 7001_ $$00000-0001-7266-9844$$aEr, Sezgin$$b3
000299517 7001_ $$0P:(DE-He78)409341d9f7e2ca20152d46e4b128a04f$$aClarke, Brian$$b4$$udkfz
000299517 7001_ $$0P:(DE-He78)9aabcfee1a1fc9202398a45a63f0b1e3$$aStegle, Oliver$$b5$$udkfz
000299517 7001_ $$00000-0001-6055-277X$$aBayraktar, Omer Ali$$b6
000299517 773__ $$0PERI:(DE-600)2163081-1$$a10.1038/s41592-025-02608-3$$n4$$p698-707$$tNature methods$$v22$$x1548-7091$$y2025
000299517 909CO $$ooai:inrepo02.dkfz.de:299517$$pVDB
000299517 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)409341d9f7e2ca20152d46e4b128a04f$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000299517 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)9aabcfee1a1fc9202398a45a63f0b1e3$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000299517 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0
000299517 9141_ $$y2025
000299517 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2025-01-07$$wger
000299517 915__ $$0StatID:(DE-HGF)3003$$2StatID$$aDEAL Nature$$d2025-01-07$$wger
000299517 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNAT METHODS : 2022$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2025-01-07
000299517 915__ $$0StatID:(DE-HGF)9940$$2StatID$$aIF >= 40$$bNAT METHODS : 2022$$d2025-01-07
000299517 9201_ $$0I:(DE-He78)B260-20160331$$kB260$$lB260 Bioinformatik der Genomik und Systemgenetik$$x0
000299517 980__ $$ajournal
000299517 980__ $$aVDB
000299517 980__ $$aI:(DE-He78)B260-20160331
000299517 980__ $$aUNRESTRICTED