Survey of Bioinformatics-Based Protein Function Prediction

doi:10.3778/j.issn.1002-8331.2212-0167

Abstract

Abstract: The protein function prediction task aims to provide functional annotations for protein data with missing functional tags. With the development of protein sequencing technology, the number of proteins in the database is growing rapidly, and due to the complexity and multiplicity of protein data, the protein function prediction task is very challenging and has received close attention from researchers. In this paper, the development history of machine learning in protein function prediction is firstly reviewed. Secondly, protein function prediction methods in recent years are categorized and summarized, and the similarities and differences between various algorithms are analyzed. Finally, the problems of protein function prediction are discussed, and future research in this field is anticipated.

Key words: protein function prediction, protein sequences, machine learning, biocomputing, bioinformatics

摘要： 蛋白质功能预测任务旨在为缺失功能标签的蛋白质数据提供功能注释，随着蛋白质测序技术的发展，数据库中蛋白质数量迅速增长，由于蛋白质数据的复杂性和多元性，蛋白质功能预测任务极具挑战，受到研究人员的密切关注。梳理了机器学习在蛋白质功能预测中的发展历程；对近年来的蛋白质功能预测方法进行归类与总结，分析各类算法之间的异同；最后对蛋白质功能预测存在的问题进行讨论，并对该领域的未来研究进行展望。

关键词: 蛋白质功能预测, 蛋白质序列, 机器学习, 生物计算, 生物信息学

LI Xinhui, QIAN Yurong, YUE Haitao, HU Yue, CHEN Jiaying, LENG Hongyong, MA Mengnan. Survey of Bioinformatics-Based Protein Function Prediction[J]. Computer Engineering and Applications, 2023, 59(16): 50-62.

李昕晖, 钱育蓉, 岳海涛, 胡月, 陈嘉颖, 冷洪勇, 马梦楠. 基于生物信息学的蛋白质功能预测研究综述[J]. 计算机工程与应用, 2023, 59(16): 50-62.

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