基于蛋白质相互作用网络的蛋白质复合物和功能模块预测算法研究进展

蛋白质相互作用网络中的模块化结构通常对应于蛋白质复合物或者蛋白质功能模块。基于蛋白质相互作用网络预测蛋白质复合物和功能模块不仅有助于理解生命有机体的细胞生物过程，而且可为探讨疾病的发生、发展和治疗以及合理的药物开发提供重要的基础。本文通过回顾近二十年来基于蛋白质相互作用网络的蛋白质复合物和功能模块预测算法研究的发展历程，按照静态蛋白质相互作用网络(SPIN)和动态蛋白质相互作用网络(DPIN)两个方向分别梳理预测算法所涉及的方法和技术，同时归纳常用的数据集并分析所面临的问题，为进一步研究提供有价值的参考。

Research Progress of Protein Complexes and Functional Modules Prediction Algorithm Based on Protein-Protein Interaction Network

The modular structure in protein-protein interaction network usually corresponds to protein complexes or protein functional modules.Prediction of protein complexes and functional modules based on protein-protein interaction networks not only helps to understand the cellular biological processes of living organisms,but also provides an important basis for exploring the occurrence,development and treatment of diseases and rational drug development.The development of protein complexes and functional modules prediction algorithms based on protein-protein interaction networks in the past two decades are reviewed in this article.The methods and techniques involved in prediction algorithms are sorted out according to the two directions of static/dynamic protein-protein interaction networks.At the same time,the commonly used data sets are summarized and the problems faced are analyzed,which provide valuable reference for further research.