DynaVelo, a neural ODE model of single-cell dynamics, published in Nature Biotechnology
anshulkundaje · x · 2026-10-23
A team led by Alireza Karbalayghareh (MSK) published DynaVelo in Nature Biotechnology: a generative neural ODE model that learns the joint dynamics of gene expression and TF motif activity from single-cell multiome data.
- Unlike trajectory-only methods, DynaVelo learns a functional vector field, enabling in silico perturbation of the model itself
- It recovers the bifurcating in vivo dynamics of murine germinal center B cells and shows how heterozygous loss of Arid1a and Ctcf alters them
- The model predicts loss-of-function and rescue perturbation outcomes in B cells
Paper (open access) and code are available.
Related event: DynaVelo Uses Neural ODEs to Predict How Perturbations Reverse Cell Fates(2 posts)→
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