Multi-resBind: a residual network-based multi-label classifier for in vivo RNA binding prediction and preference visualization.

ABSTRACT:

Background

Protein-RNA interactions play key roles in many processes regulating gene expression. To understand the underlying binding preference, ultraviolet cross-linking and immunoprecipitation (CLIP)-based methods have been used to identify the binding sites for hundreds of RNA-binding proteins (RBPs) in vivo. Using these large-scale experimental data to infer RNA binding preference and predict missing binding sites has become a great challenge. Some existing deep-learning models have demonstrated high prediction accuracy for individual RBPs. However, it remains difficult to avoid significant bias due to the experimental protocol. The DeepRiPe method was recently developed to solve this problem via introducing multi-task or multi-label learning into this field. However, this met

SUBMITTER: Zhao S 

PROVIDER: S-EPMC8594109 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature