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.
KeywordsProtein phosphorylation Kinase-substrate interactions Bi-random walk Protein-protein interaction network
This work is supported in part by the National Natural Science Foundation of China under Grant No. 61702122, 61751314, 31560317, 61702555, 61662028 and 61762087; Key project of Natural Science Foundation of Guangxi 2017GXNSFDA198033; Key research and development plan of Guangxi AB17195055 and Director Open Fund of Qinzhou City Key Laboratory of Advanced Technology of Internet of Things IOT2017A04.
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