CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms.
Ontology highlight
ABSTRACT: Linking cis-regulatory sequences to target genes has been a long-standing challenge. In this study, we introduce CREaTor, an attention-based deep neural network designed to model cis-regulatory patterns for genomic elements up to 2 Mb from target genes. Coupled with a training strategy that predicts gene expression from flanking candidate cis-regulatory elements (cCREs), CREaTor can model cell type-specific cis-regulatory patterns in new cell types without prior knowledge of cCRE-gene interactions or additional training. The zero-shot modeling capability, combined with the use of only RNA-seq and ChIP-seq data, allows for the ready generalization of CREaTor to a broad range of cell types.
SUBMITTER: Li Y
PROVIDER: S-EPMC10666311 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA