{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T01:36:32Z","timestamp":1761356192728,"version":"build-2065373602"},"reference-count":51,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T00:00:00Z","timestamp":1757462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12571306","12222111","12331009"],"award-info":[{"award-number":["12571306","12222111","12331009"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chinese University of Hong Kong startup","award":["4930181"],"award-info":[{"award-number":["4930181"]}]},{"name":"Hong Kong Research Grant Council","award":["GRF 14301120","GRF 14300923"],"award-info":[{"award-number":["GRF 14301120","GRF 14300923"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>RNA velocity has become a powerful tool for uncovering transcriptional dynamics in snapshot single-cell data. However, current RNA velocity approaches often assume constant transcriptional rates and treat genes independently with gene-specific times, which may introduce biases and deviate from biological realities. Here, we present InterVelo, a novel deep learning framework that simultaneously learns cellular pseudotime and RNA velocity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>InterVelo leverages an unsupervised cellular time to guide RNA velocity estimation, while the estimated RNA velocity in turn refines the direction of pseudotime. By benchmarking InterVelo against existing methods on both simulated and real datasets, we demonstrate its superior performance in recovering pseudotime and RNA velocity. InterVelo yields more precise velocity estimations in terms of both direction and magnitude, with outstanding robustness across diverse scenarios. Furthermore, it successfully identifies driver genes and enables reliable gene activity enrichment analysis. The flexible architecture of InterVelo also allows for the integration of multi-omic data, enhancing its applicability to complex biological systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>InterVelo is implemented using Python, and the code is available on GitHub https:\/\/github.com\/yurouwang-rosie\/InterVelo and has been archived with a DOI https:\/\/doi.org\/10.5281\/zenodo.16158798 for reproducibility.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf500","type":"journal-article","created":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T11:21:15Z","timestamp":1757330475000},"source":"Crossref","is-referenced-by-count":0,"title":["InterVelo: a mutually enhancing model for estimating pseudotime and RNA velocity in multi-omic single-cell data"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9394-9858","authenticated-orcid":false,"given":"Yurou","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , 200240 Shanghai,","place":["China"]},{"name":"SJTU-Yale Joint Center for Biostatistics and Data Science, Technical Center for Digital Medicine, National Center for Translational Medicine, Shanghai Jiao Tong University , 200240 Shanghai,","place":["China"]}]},{"given":"Zhixiang","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Statistics, The Chinese University of Hong Kong , 999077 Shatin, Hong Kong SAR,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1218-4017","authenticated-orcid":false,"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , 200240 Shanghai,","place":["China"]},{"name":"SJTU-Yale Joint Center for Biostatistics and Data Science, Technical Center for Digital Medicine, National Center for Translational Medicine, Shanghai Jiao Tong University , 200240 Shanghai,","place":["China"]},{"name":"Department of Statistics and MOE-LSC and CMA-Shanghai, School of Mathematical Sciences, Shanghai Jiao Tong University , 200240 Shanghai,","place":["China"]},{"name":"MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University , 200240 Shanghai,","place":["China"]}]}],"member":"286","published-online":{"date-parts":[[2025,9,10]]},"reference":[{"key":"2025102421321004400_btaf500-B1","first-page":"25","volume-title":"Handb Clin Neurol","author":"Accogli","year":"2020"},{"key":"2025102421321004400_btaf500-B2","first-page":"6571","article-title":"Neural ordinary differential equations","volume":"31","author":"Chen","year":"2018","journal-title":"Adv Neural Inform Process Syst"},{"key":"2025102421321004400_btaf500-B3","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"2025102421321004400_btaf500-B4","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1038\/s41592-025-02608-3","article-title":"Cell2fate infers RNA velocity modules to improve cell fate prediction","volume":"22","author":"Aivazidis","year":"2025","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B5","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1038\/s41580-019-0186-3","article-title":"Unravelling cellular relationships during development and regeneration using genetic lineage tracing","volume":"20","author":"Baron","year":"2019","journal-title":"Nat Rev Mol Cell Biol"},{"key":"2025102421321004400_btaf500-B6","doi-asserted-by":"crossref","first-page":"12328","DOI":"10.1523\/JNEUROSCI.4000-08.2008","article-title":"Specific glial populations regulate hippocampal morphogenesis","volume":"28","author":"Barry","year":"2008","journal-title":"J Neurosci"},{"key":"2025102421321004400_btaf500-B7","doi-asserted-by":"crossref","DOI":"10.1242\/dev.173849","article-title":"Comprehensive single cell mRNA profiling reveals a detailed roadmap for pancreatic endocrinogenesis","volume":"146","author":"Bastidas-Ponce","year":"2019","journal-title":"Development"},{"key":"2025102421321004400_btaf500-B8","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1126\/science.aax3072","article-title":"Sequencing metabolically labeled transcripts in single cells reveals mRNA turnover strategies","volume":"367","author":"Battich","year":"2020","journal-title":"Science"},{"key":"2025102421321004400_btaf500-B9","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1038\/s41587-020-0591-3","article-title":"Generalizing RNA velocity to transient cell states through dynamical modeling","volume":"38","author":"Bergen","year":"2020","journal-title":"Nat Biotechnol"},{"key":"2025102421321004400_btaf500-B10","doi-asserted-by":"crossref","first-page":"e10282","DOI":"10.15252\/msb.202110282","article-title":"RNA velocity-current challenges and future perspectives","volume":"17","author":"Bergen","year":"2021","journal-title":"Mol Syst Biol"},{"key":"2025102421321004400_btaf500-B11","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1038\/nchembio.2517","article-title":"Metabolomics-based discovery of a metabolite that enhances oligodendrocyte maturation","volume":"14","author":"Beyer","year":"2018","journal-title":"Nat Chem Biol"},{"key":"2025102421321004400_btaf500-B12","doi-asserted-by":"crossref","first-page":"3922","DOI":"10.1038\/s41467-018-06176-3","article-title":"Lineage dynamics of murine pancreatic development at single-cell resolution","volume":"9","author":"Byrnes","year":"2018","journal-title":"Nat Commun"},{"key":"2025102421321004400_btaf500-B14","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1186\/s13059-016-0944-x","article-title":"Single-cell epigenomics: powerful new methods for understanding gene regulation and cell identity","volume":"17","author":"Clark","year":"2016","journal-title":"Genome Biol"},{"key":"2025102421321004400_btaf500-B15","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s13059-023-03148-9","article-title":"DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics","volume":"25","author":"Cui","year":"2024","journal-title":"Genome Biol"},{"key":"2025102421321004400_btaf500-B16","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1038\/s41586-019-1369-y","article-title":"scSLAM-seq reveals core features of transcription dynamics in single cells","volume":"571","author":"Erhard","year":"2019","journal-title":"Nature"},{"key":"2025102421321004400_btaf500-B17","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1146\/annurev-cellbio-111315-124953","article-title":"Neurogenesis and gliogenesis in nervous system plasticity and repair","volume":"32","author":"Fris\u00e9n","year":"2016","journal-title":"Annu Rev Cell Dev Biol"},{"key":"2025102421321004400_btaf500-B18","doi-asserted-by":"crossref","first-page":"6586","DOI":"10.1038\/s41467-022-34188-7","article-title":"UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference","volume":"13","author":"Gao","year":"2022","journal-title":"Nat Commun"},{"key":"2025102421321004400_btaf500-B19","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1038\/s41592-023-01994-w","article-title":"Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells","volume":"21","author":"Gayoso","year":"2024","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B20","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1038\/s43586-024-00363-x","article-title":"Uniform manifold approximation and projection","volume":"4","author":"Healy","year":"2024","journal-title":"Nat Rev Methods Primers"},{"key":"2025102421321004400_btaf500-B21","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/s41593-017-0056-2","article-title":"Conserved properties of dentate gyrus neurogenesis across postnatal development revealed by single-cell RNA sequencing","volume":"21","author":"Hochgerner","year":"2018","journal-title":"Nat Neurosci"},{"key":"2025102421321004400_btaf500-B14485066","article-title":"Auto-encoding variational bayes","author":"Kingma","year":"2013","journal-title":"arXiv Preprint"},{"key":"2025102421321004400_btaf500-B22","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1038\/s41576-018-0089-8","article-title":"Chromatin accessibility and the regulatory epigenome","volume":"20","author":"Klemm","year":"2019","journal-title":"Nat Rev Genet"},{"key":"2025102421321004400_btaf500-B23","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1038\/s41586-018-0414-6","article-title":"RNA velocity of single cells","volume":"560","author":"La Manno","year":"2018","journal-title":"Nature"},{"key":"2025102421321004400_btaf500-B24","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1038\/s41592-021-01346-6","article-title":"CellRank for directed single-cell fate mapping","volume":"19","author":"Lange","year":"2022","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B25","doi-asserted-by":"crossref","first-page":"2271","DOI":"10.1038\/s41592-024-02471-8","article-title":"Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations","volume":"21","author":"Lederer","year":"2024","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B26","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1038\/s41587-022-01476-y","article-title":"Multi-omic single-cell velocity models epigenome-transcriptome interactions and improves cell fate prediction","volume":"41","author":"Li","year":"2023","journal-title":"Nat Biotechnol"},{"key":"2025102421321004400_btaf500-B27","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1186\/s13059-023-02988-9","article-title":"scTour: a deep learning architecture for robust inference and accurate prediction of cellular dynamics","volume":"24","author":"Li","year":"2023","journal-title":"Genome Biol"},{"key":"2025102421321004400_btaf500-B28","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1038\/s41587-023-01728-5","article-title":"A relay velocity model infers cell-dependent RNA velocity","volume":"42","author":"Li","year":"2024","journal-title":"Nat Biotechnol"},{"key":"2025102421321004400_btaf500-B29","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1038\/s41467-022-35574-x","article-title":"Single-cell transcriptomic analysis reveals diversity within mammalian spinal motor neurons","volume":"14","author":"Liau","year":"2023","journal-title":"Nat Commun"},{"key":"2025102421321004400_btaf500-B30","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1016\/S0896-6273(03)00116-8","article-title":"Neuronal or glial progeny: regional differences in radial glia fate","volume":"37","author":"Malatesta","year":"2003","journal-title":"Neuron"},{"key":"2025102421321004400_btaf500-B31","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1038\/s41416-023-02468-8","article-title":"The cyclin-dependent kinase 1: more than a cell cycle regulator","volume":"129","author":"Massacci","year":"2023","journal-title":"Br J Cancer"},{"key":"2025102421321004400_btaf500-B32","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1111\/joa.13055","article-title":"New insights into the development of the human cerebral cortex","volume":"235","author":"Moln\u00e1r","year":"2019","journal-title":"J Anat"},{"key":"2025102421321004400_btaf500-B33","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.cell.2012.12.018","article-title":"Latent enhancers activated by stimulation in differentiated cells","volume":"152","author":"Ostuni","year":"2013","journal-title":"Cell"},{"key":"2025102421321004400_btaf500-B34","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s12551-023-01090-5","article-title":"Studying temporal dynamics of single cells: expression, lineage and regulatory networks","volume":"16","author":"Pan","year":"2024","journal-title":"Biophys Rev"},{"key":"2025102421321004400_btaf500-B35","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.fertnstert.2019.08.090","article-title":"Steroid hormones and hormone antagonists regulate the neural marker neurotrimin in uterine leiomyoma","volume":"113","author":"Parikh","year":"2020","journal-title":"Fertil Steril"},{"key":"2025102421321004400_btaf500-B36","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1038\/s41592-020-0935-4","article-title":"Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq","volume":"17","author":"Qiu","year":"2020","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B37","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1038\/nmeth.4402","article-title":"Reversed graph embedding resolves complex single-cell trajectories","volume":"14","author":"Qiu","year":"2017","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B38","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.cels.2020.02.003","article-title":"Inferring causal gene regulatory networks from coupled single-cell expression dynamics using scribe","volume":"10","author":"Qiu","year":"2020","journal-title":"Cell Syst"},{"key":"2025102421321004400_btaf500-B39","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1016\/j.cell.2021.12.045","article-title":"Mapping transcriptomic vector fields of single cells","volume":"185","author":"Qiu","year":"2022","journal-title":"Cell"},{"key":"2025102421321004400_btaf500-B40","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1038\/s41587-024-02186-3","article-title":"Gene trajectory inference for single-cell data by optimal transport metrics","volume":"43","author":"Qu","year":"2025","journal-title":"Nat Biotechnol"},{"key":"2025102421321004400_btaf500-B41","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1038\/nature09692","article-title":"A unique chromatin signature uncovers early developmental enhancers in humans","volume":"470","author":"Rada-Iglesias","year":"2011","journal-title":"Nature"},{"key":"2025102421321004400_btaf500-B42","doi-asserted-by":"crossref","first-page":"174103","DOI":"10.1063\/1.5064530","article-title":"Generalized markov modeling of nonreversible molecular kinetics","volume":"150","author":"Reuter","year":"2019","journal-title":"J Chem Phys"},{"key":"2025102421321004400_btaf500-B43","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/1749-8104-9-14","article-title":"Transcriptional control of GABAergic neuronal subtype identity in the thalamus","volume":"9","author":"Sellers","year":"2014","journal-title":"Neural Dev"},{"key":"2025102421321004400_btaf500-B44","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/s41587-019-0068-4","article-title":"Characterization of cell fate probabilities in single-cell data with palantir","volume":"37","author":"Setty","year":"2019","journal-title":"Nat Biotechnol"},{"key":"2025102421321004400_btaf500-B45","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/j.cels.2024.04.005","article-title":"Causal gene regulatory analysis with RNA velocity reveals an interplay between slow and fast transcription factors","volume":"15","author":"Singh","year":"2024","journal-title":"Cell Syst"},{"key":"2025102421321004400_btaf500-B46","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1186\/s12864-018-4772-0","article-title":"Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics","volume":"19","author":"Street","year":"2018","journal-title":"BMC Genomics"},{"key":"2025102421321004400_btaf500-B47","doi-asserted-by":"crossref","first-page":"5053","DOI":"10.1016\/j.cell.2021.07.039","article-title":"Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution","volume":"184","author":"Trevino","year":"2021","journal-title":"Cell"},{"key":"2025102421321004400_btaf500-B48","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1038\/nrg2781","article-title":"Inducible gene expression: diverse regulatory mechanisms","volume":"11","author":"Weake","year":"2010","journal-title":"Nat Rev Genet"},{"key":"2025102421321004400_btaf500-B49","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.1038\/s41592-024-02303-9","article-title":"CellRank 2: unified fate mapping in multiview single-cell data","volume":"21","author":"Weiler","year":"2024","journal-title":"Nat Methods"},{"key":"2025102421321004400_btaf500-B50","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1186\/s13059-019-1663-x","article-title":"PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells","volume":"20","author":"Wolf","year":"2019","journal-title":"Genome Biol"},{"key":"2025102421321004400_btaf500-B51","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1186\/s13059-023-03065-x","article-title":"Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates","volume":"24","author":"Zheng","year":"2023","journal-title":"Genome Biol"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaf500\/64237123\/btaf500.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/41\/10\/btaf500\/64237123\/btaf500.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/41\/10\/btaf500\/64237123\/btaf500.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T01:32:25Z","timestamp":1761355945000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btaf500\/8250681"}},"subtitle":[],"editor":[{"given":"Christina","family":"Kendziorski","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2025,9,10]]},"references-count":51,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaf500","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2025,10]]},"published":{"date-parts":[[2025,9,10]]},"article-number":"btaf500"}}