预测蛋白质亚细胞定位的杂交系统

Shu-Bo Zhang, J. Lai
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引用次数: 0

摘要

蛋白质亚细胞定位预测是蛋白质功能解释的重要内容。本研究提出了一种基于蛋白质分选机制的杂交系统来预测蛋白质亚细胞定位。首先,将未知蛋白质序列在特定位置划分为两个子序列,然后从中提取特征并组合成一个融合特征向量来描述整个蛋白质序列。其次,通过迭代搜索策略,找出最优子分类器,将每种蛋白质与其他蛋白质区分开来;最后,将所有的亚分类器组合成一个杂交系统来预测未知蛋白的亚细胞定位。在两个公开数据集上的实验结果表明,该混合系统是一种有效的蛋白质亚细胞定位预测方法,具有较高的准确性。
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A Hybrid System for Prediction of Protein Subcellular Localization
Protein subcellular localization prediction is important to functional annotation of protein. In this study, a hybrid system based on the sorting mechanism of protein was proposed to predict protein subcellular localization. At first, an unknown protein sequence was divided into two sub-sequences at certain position, then features were extracted from them and combined into a fusion feature vector to describe the whole protein sequence. Secondly, an optimal sub-classifier was searched out to discriminate each kind of protein from the others through iterative searching strategy. Finally, all of the sub-classifiers were combined into a hybrid system to predict subcellular localization of unknown protein. Experimental results on two public datasets showed that our hybrid system is an effective way for the prediction of protein subcellular localization, and it has higher accuracy than others.
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