Comprehensive Survey and Comparative Assessment of RNA-Binding Residue Predictions with Analysis by RNA Type.

ABSTRACT: With close to 30 sequence-based predictors of RNA-binding residues (RBRs), this comparative survey aims to help with understanding and selection of the appropriate tools. We discuss past reviews on this topic, survey a comprehensive collection of predictors, and comparatively assess six representative methods. We provide a novel and well-designed benchmark dataset and we are the first to report and compare protein-level and datasets-level results, and to contextualize performance to specific types of RNAs. The methods considered here are well-cited and rely on machine learning algorithms on occasion combined with homology-based prediction. Empirical tests reveal that they provide relatively accurate predictions. Virtually all methods perform well for the proteins that interact with rRNAs,

SUBMITTER: Wang K 

PROVIDER: S-EPMC7554811 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature