Inferring fungal cis-regulatory networks from genome sequences via unsupervised and interpretable representation learning.

ABSTRACT: Gene expression patterns are determined to a large extent by transcription factor (TF) binding to noncoding regulatory regions in the genome. However, gene expression cannot yet be systematically predicted from genome sequences, in part because nonfunctional matches to the sequence patterns (motifs) recognized by TFs occur frequently throughout the genome. Large-scale functional genomics data for many TFs has enabled characterization of regulatory networks in experimentally accessible cells such as budding yeast. Beyond yeast, fungi are important industrial organisms and pathogens, but large-scale functional data is only sporadically available. Uncharacterized regulatory networks control key pathways and gene expression programs associated with fungal phenotypes. Here, we explore a sequenc

SUBMITTER: Moses AM 

PROVIDER: S-EPMC12774827 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature