EnsembleSE: identification of super-enhancers based on ensemble learning.

ABSTRACT: Super-enhancers (SEs) are typically located in the regulatory regions of genes, driving high-level gene expression. Identifying SEs is crucial for a deeper understanding of gene regulatory networks, disease mechanisms, and the development and physiological processes of organisms, thus exerting a profound impact on research and applications in the life sciences field. Traditional experimental methods for identifying SEs are costly and time-consuming. Existing methods for predicting SEs based solely on sequence data use deep learning for feature representation and have achieved good results. However, they overlook biological features related to physicochemical properties, leading to low interpretability. Additionally, the complex model structure often requires extensive labeled data for trai

SUBMITTER: He W 

PROVIDER: S-EPMC12008123 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature