基于生物信息学的蛋白质功能预测方法研究进展

Advances in bioinformatics-based protein function prediction

随着计算能力的增加和生物数据的快速扩展,利用生物信息学解决一些生物学问题逐渐成为主流的解决方案。蛋白质功能预测是生物医学和药物研究领域的重要任务。利用生物信息学进行蛋白质功能预测成为研究热点。本文将基于生物信息学的蛋白质功能预测方法归纳为3类:基于蛋白质序列的方法、基于蛋白质结构的方法和基于蛋白质相互作用网络的方法,并进一步分析和总结了这些方法的具体算法以及最新研究进展,为生物医学和药物研究领域深入探索预测蛋白质功能提供重要参考。

With the increasing of computer power and rapid expansion of biological data,the application of bioinformatics tools has become the mainstream approach to address biological problems.The accurate identification of protein function by bioinformatics tools is crucial for both biomedical research and drug discovery,making it a hot topic of research.In this paper,we categorize bioinformatics-based protein function prediction methods into three categories:protein sequence-based methods,protein structure-based methods,and protein interaction networks-based methods.We further analyze these specific algorithms,highlighting the latest research advancements and providing valuable references for the application of bioinformatics-based protein function prediction in biomedical research and drug discovery.