RNet: a network strategy to predict RNA binding preferences.

ABSTRACT: Determining the RNA binding preferences remains challenging because of the bottleneck of the binding interactions accompanied by subtle RNA flexibility. Typically, designing RNA inhibitors involves screening thousands of potential candidates for binding. Accurate binding site information can increase the number of successful hits even with few candidates. There are two main issues regarding RNA binding preference: binding site prediction and binding dynamical behavior prediction. Here, we propose one interpretable network-based approach, RNet, to acquire precise binding site and binding dynamical behavior information. RNetsite employs a machine learning-based network decomposition algorithm to predict RNA binding sites by analyzing the local and global network properties. Our research focu

SUBMITTER: Liu H 

PROVIDER: S-EPMC10749790 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature