基于改进的GO-PseAA方法的凋亡蛋白亚细胞定位

Using Improved GO-PseAA Predictor to Predict the Subcellular Location of Apoptosis Proteins

亚细胞定位与蛋白质的功能紧密相关,细胞凋亡蛋白在生物体的发育和平衡状态中起着重要的作用,因此预测凋亡蛋白的亚细胞定位是十分有意义的。本文采用一种融合GO分子功能信息和伪氨基酸组分信息的杂合算法即GO-PseAA方法,来预测凋亡蛋白亚细胞定位。采用与Chen等相同的数据集和Jackknife检验,预测成功率达到了91.4%,结果表明本文采用的改进的GO-PseAA方法是预测凋亡蛋白亚细胞位置的一种很有效的方法。

Apoptosis proteins have a central role in the development and the homeostasis of an organism, and there is a close relationship between the function and the subcellular location of protein, so it is very impor- tant to predict the subcellular location of apoptosis proteins. In this paper, we predict the subcellular location of apoptosis proteins by hybridizing the gene ontology approach and the pseudo -amino acid composition ap- proach. The jackknife is performed on Chens dataset. The overall prediction accuracy reaches 91.4%. The re- sult indicates that using this method to represent protein sample for statistical prediction is indeed very promis- ing and will become a powerful tool in bioinformatics and proteomics.