Article

scDiffEq: drift-diffusion modeling of single-cell dynamics with neural stochastic differential equations

2023-12-08

Abstract excerpt

Single-cell sequencing measurements facilitate the reconstruction of dynamic biology by capturing snapshot molecular profiles of individual cells. Cell fate decisions in development and disease are orchestrated through an intricate balance of deterministic and stochastic regulatory events. Drift-diffusion equations are effective in modeling single-cell dynamics from high-dimensional single-cell measurements. While...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d5155717-69ca-5353-973d-3551965fb5af
DOI: 10.1101/2023.12.06.570508

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

scDiffEq: drift-diffusion modeling of single-cell dynamics with neural stochastic differential equationsDOI 10.1101/2023.12.06.570508Read

ARTEMIS integrates autoencoders and Schrödinger Bridges to predict continuous dynamics of gene expression, cell population and perturbation from time-series single-cell dataSemantic proximity Read

Pseudodynamics+: Reconstructing Population Dynamics from Time-Resolved Single Cell Landscapes with Physics Informed Neural NetworksSemantic proximity Read

Building dynamical models of multi-step state transitions from single cell gene expression trajectoriesSemantic proximity Read

Learning dynamics by computational integration of single cell genomic and lineage informationSemantic proximity Read

Learning dynamics by computational integration of single cell genomic and lineage informationSemantic proximity Read

scMTG reconstructs single-cell temporal dynamics with Markov transition generatorsSemantic proximity Read

Lineage-aware stochastic modeling reveals gene-expression dynamics in development and diseaseSemantic proximity Read

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural networkSemantic proximity Read

Deep Lineage: Single-Cell Lineage Tracing and Fate Inference Using Deep LearningSemantic proximity Read

Generating and navigating single cell dynamics via a geodesic bridge between nonlinear transcriptional and linear latent manifoldsSemantic proximity Read

Generating and navigating single cell dynamics via a geodesic bridge between nonlinear transcriptional and linear latent manifoldsSemantic proximity Read

Joint Trajectory Inference for Single-cell Genomics Using Deep Learning with a Mixture PriorSemantic proximity Read