PredPRBA: Prediction of Protein-RNA Binding Affinity Using Gradient Boosted Regression Trees.

ABSTRACT: Protein-RNA interactions play essential roles in many biological aspects. Quantifying the binding affinity of protein-RNA complexes is helpful to the understanding of protein-RNA recognition mechanisms and identification of strong binding partners. Due to experimentally measured protein-RNA binding affinity data available is still limited to date, there is a pressing demand for accurate and reliable computational approaches. In this paper, we propose a computational approach, PredPRBA, which can effectively predict protein-RNA binding affinity using gradient boosted regression trees. We build a dataset of protein-RNA binding affinity that includes 103 protein-RNA complex structures manually collected from related literature. Then, we generate 37 kinds of sequence and structural features an

SUBMITTER: Deng L 

PROVIDER: S-EPMC6688581 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature