ArticleNature communications2024
TFvelo: gene regulation inspired RNA velocity estimation.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 36 citations in OpenAlex.
- Decoding epithelial-mesenchymal transitions with multi-omics.Nature reviews. Genetics · 2026Review
- Article
- Comprehensive benchmarking of RNA velocity methods across single-cell datasets.Genome biology · 2026Article
- ArchVelo: archetypal velocity modeling for single-cell multi-omic trajectories.Nature communications · 2026Article
- Challenges and progress in RNA velocity: Comparative analysis across multiple biological contexts.PLoS computational biology · 2026Article
- A Single-Cell Analysis Reveals Macrophage Heterogeneity Driving Plaque Vulnerability in Coronary and Carotid Arteries.Journal of atherosclerosis and thrombosis · 2026Article
- Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.Molecular systems biology · 2026Article
- C-C Chemokine Receptor 4 Deficiency Protects Against Abdominal Aortic Aneurysm Formation.Journal of the American Heart Association · 2026Article
- Spatial and Single-Cell Transcriptomics Reveal Keratinocytes as Key Players in Vulvar Lichen Sclerosus Pathogenesis.The Journal of investigative dermatology · 2026Article
- Article
- Fundamental errors in RNA velocity arising from the omission of cell growth.bioRxiv : the preprint server for biology · 2025Article
- Single cell spatial transcriptomics integration deciphers the morphological heterogeneity of atherosclerotic carotid arteries.Nature communications · 2025Article
- Perspectives on integrating artificial intelligence and single-cell omics for cellular plasticity research.Quantitative biology (Beijing, China) · 2025Article
- Simultaneously infer cell pseudotime, velocity field, and gene interaction from multi-branch scRNA-seq data with scPN.NAR genomics and bioinformatics · 2025Article
- Branch-specific gene discovery in cell differentiation using multi-omics graph attention.PLoS computational biology · 2025Article
- GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells.Nature communications · 2025Article
- TIVelo: RNA velocity estimation leveraging cluster-level trajectory inference.Nature communications · 2025Article
- Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review.Briefings in bioinformatics · 2025Review
- Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-Seq Data Analysis.Entropy (Basel, Switzerland) · 2025Review
- KSRV: a Kernel PCA-Based framework for inferring spatial RNA velocity at single-cell resolution.Frontiers in genetics · 2025Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
RNA velocity is closely related with cell fate and is an important indicator for the prediction of cell states with elegant physical explanation derived from single-cell RNA-seq data. Most existing RNA velocity models aim to extract dynamics from the phase delay between unspliced and spliced mRNA for each individual gene. However, unspliced/spliced mRNA abundance may not provide sufficient signal for dynamic modeling, leading to poor fit in phase portraits. Motivated by the idea that RNA velocity could be driven by the transcriptional regulation, we propose TFvelo, which expands RNA velocity concept to various single-cell datasets without relying on splicing information, by introducing gene regulatory information. Our experiments on synthetic data and multiple scRNA-Seq datasets show that TFvelo can accurately fit genes dynamics on phase portraits, and effectively infer cell pseudo-time and trajectory from RNA abundance data. TFvelo opens a robust and accurate avenue for modeling RNA velocity for single cell data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.