生物信息学方法预测蛋白质相互作用网络中的功能模块

蛋白质相互作用是大多数生命过程的基础。随着高通量实验技术和计算机预测方法的发展,在各种生物中已获得了数目十分庞大的蛋白质相互作用数据,如何从中提取出具有生物学意义的数据是一项艰巨的挑战。从蛋白质相互作用数据出发获得相互作用网络进而预测出其中的功能模块,对于蛋白质功能预测、揭示各种生化反应过程的分子机理都有着极大的帮助。我们分类概括了用生物信息学预测蛋白质相互作用功能模块的方法,以及对这些方法的评价,并介绍了蛋白质相互作用网络比较的一些方法。

Prediction of Functional Modules from Protein-Protein Interaction Network by Bioinformatics Method

Protein-protein interactions（PPIs） are the foundation of most biological processes. With the development of high-throughput experimental methods and computational prediction methods, a large amount of PPIs are available from different species. From these PPIs, it is a great challenge to abstract biological meaningful information. Started with PPIs data, PPIs network is mapped. Prediction of functional modules from PPIs network map will faeilitates prediction of protein function and elucidations of molecular mechanisms of biochemical processes. In this paper, we reviewed bioinformaties methods to predict funetional modules in PPIs network, as well as evaluation of these methods. Methods of PPIs network eomoarison were also discussed here.