生物信息学Issue(2)：103-110,8.DOI:10.3969/j.issn.1672-5565.2015.02.05
基于氨基酸约化和统计特征的蛋白质亚细胞定位预测
Protein subcellular localization prediction based on reduced representation of amino acid and statistical characteristic
摘要
Abstract
The protein subcellular localization prediction is important to study the protein function, protein interaction and their regulation mechanism. In this paper, based on four amino acids physicochemical properties and structural properties, We describe the local and global information of sequence by ‘component ’ , ‘transition ’ and‘distribution’ . Using the numerical statistical characteristic of hydrophobic/hydrophilic amino acid, we proposed a new protein feature representation. We compare the prediction results between the proposed methods and fusion method with the classification algorithm KNN, SVM and BP . The results show that fusion method with SVM can get better prediction accuracies. Meantime, we also discuss the effects of different parameters on the experimental results. The detailed experimental and comparison results show the effectiveness of the proposed method.关键词
蛋白质亚细胞定位/氨基酸物化性质/支持向量机Key words
Subcellular localization/Physicochemical properties/Support vector machine ( SVM)分类
生物科学引用本文复制引用
杨红,徐慧敏,严寿江,陈静,耿丽丽,姚玉华..基于氨基酸约化和统计特征的蛋白质亚细胞定位预测[J].生物信息学,2015,(2):103-110,8.基金项目
国家自然基金项目（61272312）资助。 （）
