ArticleGenome biology2024
DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
43 citing papers in PubMed.
- FlowMap: Geometry-Dynamics Consistent Embedding of RNA Velocity for Interpretable Cellular Trajectories.bioRxiv : the preprint server for biology · 2026Article
- Article
- Comprehensive benchmarking of RNA velocity methods across single-cell datasets.Genome biology · 2026Article
- Dissecting and steering cell dynamics using spatially-informed RNA velocity with veloAgent.Molecular systems biology · 2026Article
- VeloRM: disentangling pre- and post-splicing RNA modification dynamics at single-cell resolution.Nucleic acids research · 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
- Flow Matching for Count Data.ArXiv · 2026Article
- Predicting trajectories of illness using RNA velocity of whole blood.Nature communications · 2026Observational
- STEER: decoupling kinetics with Spatial-Temporal Explainable Expert model for RNA velocity inference.National science review · 2026Article
- Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.Molecular systems biology · 2026Article
- Topological velocity inference from spatial transcriptomic data.Nature biotechnology · 2026Article
- Benchmarking RNA velocity methods across 17 independent studies.Cell reports methods · 2026Article
- stVCR: spatiotemporal dynamics of single cells.Nature methods · 2026Article
- Bayesian inference of RNA velocity incorporating timepoints, lineage bifurcations, and count data.PLoS computational biology · 2026Article
- Article
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- RNAPaceDB: a dedicated database to dissect RNA velocity across diverse cell types.Nucleic acids research · 2026Article
- Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Inferring differential dynamics from multi-lineage, multi-omic, and multi-sample single-cell data with MultiVeloVAE.Nature communications · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes these limitations by generalizing RNA velocity to cell populations containing time-dependent kinetics and multiple lineages. DeepVelo infers time-varying cellular rates of transcription, splicing, and degradation, recovers each cell's stage in the differentiation process, and detects functionally relevant driver genes regulating these processes. Application to various developmental and pathogenic processes demonstrates DeepVelo's capacity to study complex differentiation and lineage decision events in heterogeneous scRNA-seq 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.