基于SVM的革兰氏阴性菌分泌系统蛋白识别方法

A SVM based approach to identification of Gram-negative bacterial secretion system proteins

摘要:

本文提出了一种基于SVM快速识别革兰氏阴性菌分泌系统蛋白的方法.该方法以氨基酸组成和位置特异性得分矩阵为最优特征集，充分考虑了蛋白质的序列信息及进化信息.实验结果表明，本文提出的方法对革兰氏阴性菌分泌系统蛋白具有较好的预测性能，可作为细菌分泌系统研究的有益补充.

Abstract:

A SVM based approach is proposed to rapidly identify Gram-negative bacterial secretion system proteins. With the optimization feature set consisted of amino acid composition (AAC) and position specific scoring matrix (PSSM), this method adequately takes sequence and evolution information of proteins into account. Experiments show that this method has a good performance on prediction of Gram-negative bacterial secretion system proteins, which served as a useful complement to the study of bacterial secretion system.