ARTEMIS integrates autoencoders and Schrodinger Bridges to predict continuous dynamics of gene expression, cell population, and perturbation from time-series single-cell data.

ABSTRACT:

Summary

Cellular processes like development, differentiation, and disease progression are highly complex and dynamic (e.g. gene expression). These processes often undergo cell population changes driven by cell birth, proliferation, and death. Single-cell sequencing enables gene expression measurement at the cellular resolution, allowing us to decipher cellular and molecular dynamics underlying these processes. However, the high costs and destructive nature of sequencing restrict observations to snapshots of unaligned cells at discrete timepoints, limiting our understanding of these processes and complicating the reconstruction of cellular trajectories. To address this challenge, we propose ARTEMIS, a generative model integrating a variational autoencoder (VAE) with unbalanced Diffu

SUBMITTER: Alatkar SA 

PROVIDER: S-EPMC12261462 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature