Machine Learning Methods in Prediction of Protein Palmitoylation Sites: A Brief Review

Author:

Li Yanwen1,Pu Feng1,Wang Jingru1,Zhou Zhiguo1,Zhang Chunhua1,He Fei1,Ma Zhiqiang1,Zhang Jingbo1

Affiliation:

1. School of Information Science and Technology, Northeast Normal University, Changchun 130117, China

Abstract

Protein palmitoylation is a fundamental and reversible post-translational lipid modification that involves a series of biological processes. Although a large number of experimental studies have explored the molecular mechanism behind the palmitoylation process, the computational methods has attracted much attention for its good performance in predicting palmitoylation sites compared with expensive and time-consuming biochemical experiments. The prediction of protein palmitoylation sites is helpful to reveal its biological mechanism. Therefore, the research on the application of machine learning methods to predict palmitoylation sites has become a hot topic in bioinformatics and promoted the development in the related fields. In this review, we briefly introduced the recent development in predicting protein palmitoylation sites by using machine learningbased methods and discussed their benefits and drawbacks. The perspective of machine learning-based methods in predicting palmitoylation sites was also provided. We hope the review could provide a guide in related fields.

Funder

Technology Development Planning of Jilin Province

Fundamental Research Funds for the Central Universities

Education Department of Jilin Province

Jilin Scientific and Technological Development Program

National Natural Science Funds of China

Publisher

Bentham Science Publishers Ltd.

Subject

Drug Discovery,Pharmacology

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