KSIBW: Predicting Kinase-Substrate Interactions Based on Bi-random Walk.

Protein phosphorylation is an important chemical modification in the organism that regulates many cellular processes. In recent years, many algorithms for predicting kinase-substrate interactions have been proposed. However, most of those methods are mainly focused on utilizing protein sequence information. In this paper, we propose a computational framework, KSIBW, to predict kinase-substrate interactions based on bi-random walk. Unlike traditional methods, the protein-protein interaction (PPI) information are used to measure the similarities of kinase-kinase and substrate-substrate, respectively. Then, the bi-random walk is employed to identify potential kinase-substrate interactions. The experiment results show that our method outperforms other state-of-the-art algorithms in performance.