利用支持向量机和蛋白质非稳定性指标预测凋亡蛋白类型  

Support vector machine for predicting apoptosis proteins types by incorporating protein instability index

作　　者：黄静[1] 石峰[2] 周怀北[1] 

机构地区：[1]武汉大学计算机学院,湖北武汉430072 [2]武汉大学数学与统计学院,湖北武汉430072

出　　处：《生物信息学》2005年第3期121-123,共3页Chinese Journal of Bioinformatics

基　　金：国家自然科学基金资助课题(30170214)

摘　　要：细胞凋亡蛋白对生物体的发育和体内稳定、对人们理解程序细胞凋亡的机制非常重要。根据在细胞中的位置,它们一般分为四种类型。文中利用支持向量机和蛋白质的非稳定性指标对98个细胞凋亡蛋白进行分类,取得了较好的结果。Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death. They can be classified among the following four types. The Support Vector Machine is applied for predicting the type of a given apoptosis protein by incorporating the Protein instability index in this paper. High success rates were obtained by this method.

关 键 词：凋亡蛋白类型 支持向量机 非稳定性指标 

分 类 号：Q811.2[生物学—生物工程]