基于氨基酸索引数据库数据挖掘的凋亡蛋白亚细胞定位预测

Zhuoxing Shi, Qi Dai, P. He, Yu-Hua Yao, Bo Liao
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引用次数: 1

摘要

本文在ACF模型和SVM分类器的基础上,成功地进行了试验信息挖掘,发现采用疏水性对细胞凋亡蛋白的亚细胞定位预测分析更为有效。利用ACF模型和SVM对aindex数据库进行扫描,得到了三个基准数据集的这一信息,aindex数据库包含544种氨基酸。本工作的贡献在于首次全面研究了氨基酸指数对凋亡蛋白亚细胞定位的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Subcellular localization prediction of apoptosis proteins based on the data mining for amino acid index database
In this work, based on the ACF model and the SVM classifier, succeeded on trials mining information that it's more effective to analyze the subcellular localization prediction of apoptosis proteins when adopting hydrophobicity property. This information is obtained in three benchmark datasets by using the ACF model and SVM to scan the AAindex database, which contains 544 kinds of amino acids. The contribution of this work is that it first did a comprehensive research on the effectiveness of the amino acid index for the subcellular localization of apoptosis proteins.
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