RWDisEnh+: Enhancing disease-enhancer association prediction through multiplex-heterogeneous networks.

ABSTRACT: Enhancers are critical regulatory DNA elements that, when dysregulated, can contribute to disease pathogenesis by altering gene expression. Although millions of enhancers have been identified through large-scale genomic projects, their associations with human diseases remain largely uncharacterized, emphasizing the need for robust computational approaches. In our previous work, we developed RWDisEnh, a network-based method that integrates a shared gene-based enhancer network with a disease similarity network within a heterogeneous framework to predict disease-enhancer associations. In this study, we present RWDisEnh+ , an enhanced version of RWDisEnh that incorporates a sequence-based enhancer similarity network into a multiplex-heterogeneous network to improve prediction performance. Usin

SUBMITTER: Le DH 

PROVIDER: S-EPMC12923038 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature