基于二级结构信息的蛋白质相互作用贝叶斯分类预测  

Predicting protein-protein interaction based on protein secondary structure information using Bayesian classifier

作　　者：秦笙[1] 蔡禄[1] 

机构地区：[1]内蒙古科技大学数理与生物工程学院,内蒙古包头014010

出　　处：《内蒙古科技大学学报》2010年第1期80-83,共4页Journal of Inner Mongolia University of Science and Technology

基　　金：国家自然科学基金资助项目(60761001)

摘　　要：蛋白质相互作用在许多生物学过程中扮演重要角色.蛋白质直接相互作用依赖其空间结构,蛋白质二级结构作为其空间结构的基本元件应该包含相互作用的信息.基于相互作用蛋白对二级结构信息,提出一个蛋白质相互作用的贝叶斯分类器预测模型.对酵母、人类数据的开放测试和对小鼠、果蝇的独立集测试的初步预测分别取得59.16%和59.85%的精确度,这表明蛋白质二级结构信息和贝叶斯分类器的确可以用于蛋白质相互作用预测.Protein-protein interaction （PPI） plays an important role in many biological processes. The PPI depends on space structures of proteins. As a basic element of protein structure, secondary structures should contain information of PPIs. A new approach was introduced to predict the interaction of proteins solely by analyzing their secondary structures, and the predicting model was built based on Bayesian classifier. The model achieved a significant performance with prediction accuracy of 59.16% and 59.85% in open test for S. cerevisiae,human and in independent set test for mouse and D. rnelanogaster, respectively. The result shows that the relationship between secondary structures of proteins and Bayesian classifier can be used to predict protein-protein interaction.

关 键 词：蛋白质相互作用 二级结构 贝叶斯分类 

分 类 号：Q617[生物学—生物物理学]