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作 者:余乐正[1] 陈曼[1] 赵柳青[1] 罗杰斯[2] 柳凤娟[1]
机构地区:[1]贵州师范学院化学与生命科学学院,贵州贵阳550018 [2]四川大学化学学院,四川成都610065
出 处:《化学研究与应用》2015年第7期969-973,共5页Chemical Research and Application
基 金:贵州省科学技术基金计划项目(黔科合J字[2014]2134号)资助;贵州师范学院校级博士项目(12BS024)资助;贵州师范学院校级大学生科研项目(2013DXS061)资助
摘 要:革兰氏阴性菌细胞中至少存在八种分泌系统,而每种分泌系统分别由一系列具有特定结构与功能的蛋白质组成。因此,对不同类型的细菌分泌系统蛋白进行深入研究,不仅有助于理解对应的蛋白质分泌机制,对于疾病的诊断与治疗及新药研发也具有重要意义。以氨基酸组成和位置特异性得分矩阵为替代模型,本文构建了一个基于支持向量机构的多元分类器以快速区分不同类型的革兰氏阴性菌分泌系统蛋白。实验结果表明,本方法对I、II及V型分泌系统蛋白具有较好的预测性能。There are at least eight secretion systems existing in Gram-negative bacterial cells,and each secretion system consists of a series of proteins with specific structure and function. So an in-depth study for different types of bacterial secretion system proteins is not only useful for understanding of the corresponding protein secretion mechanisms,but also has the vital significance to the diagnosis and therapy of diseases and the development of new drugs. Using the substitution model composed of amino acid composition( AAC) and position specific scoring matrix( PSSM),a multi-classifier based on support vector machine( SVM) is proposed to rapidly distinguish different types of Gram-negative bacterial secretion system proteins in this paper. It is proved that the performance of our method in predicting type I secretion system proteins( T1SSPs),type II secretion system proteins( T2SSPs) and type V secretion system proteins( T5SSPs) is satisfactory.
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