CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions.

ABSTRACT: Cell fate decisions are orchestrated by intricate gene regulatory networks (GRNs), which govern gene expression with precise spatiotemporal control. However, accurately capturing context-specific nature of gene regulation remains challenging, particularly when integrating multi-omics data at bulk and single-cell level across diverse cellular contexts. Here, we present CellPolaris, a unified computational framework designed to decode the roles of transcription factors (TFs) in developmental processes. CellPolaris performs TF-centered GRN construction, master TF identification, and TF perturbation simulation. By leveraging transfer learning, the framework generates tissue-specific or cell-type-specific GRNs using pre-constructed high-confidence GRNs of diverse contexts and requires only tran

SUBMITTER: Feng G 

PROVIDER: S-EPMC12948241 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature