大连理工大学学报2012，Vol.52Issue(3)：426-430,5.
PCA方法在蛋白质亚细胞定位中应用
Application of PCA method to predicting protein subcellular location
马军伟 1史舵 2顾宏 2张杰3
作者信息
- 1. 大连理工大学控制科学与工程学院,辽宁大连116024／山西省电力公司电力通信中心,山西太原030001
- 2. 大连理工大学控制科学与工程学院,辽宁大连116024
- 3. 安徽工业大学数理学院,安徽马鞍山243002
- 折叠
摘要
Abstract
The location of a protein subcellular is closely correlated with its biological function. With the rapid expansion of protein databases, it is very important to design a powerful high-throughput algorithm for predicting protein subcellular location. Many prediction tools have been designed based on the pseudo-amino acid composition, and a data analysis method, principal component analysis （PCA） method, is applied to determining in advance the optimal value of ~ which reflects sequence order effects. Firstly, the parameter 2 is set to the maximum to contain more sequence order information; then, PCA is employed to extract the essential features. Experimental results show that the proposed method solves the above problem, and its performance is better than those of other predictors.关键词
蛋白质亚细胞定位/主成分分析/伪氨基酸组成/k近邻分类器/BP神经网络Key words
protein subcellular location/principal component analysis/pseudo-amino acid composition/k-NN classifier/BP neural network分类
信息技术与安全科学引用本文复制引用
马军伟,史舵,顾宏,张杰..PCA方法在蛋白质亚细胞定位中应用[J].大连理工大学学报,2012,52(3):426-430,5.
