计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (15): 226-229.DOI: 10.3778/j.issn.1002-8331.2010.15.067

• 工程与应用 • 上一篇    下一篇

元胞自动机图的蛋白质二级结构类型预测

胡鸿豪,宋丽平,肖 绚   

  1. 景德镇陶瓷学院 机电学院,江西 景德镇 333001
  • 收稿日期:2008-11-16 修回日期:2009-02-09 出版日期:2010-05-21 发布日期:2010-05-21
  • 通讯作者: 胡鸿豪

Secondary structure prediction by GLCM of CAI

HU Hong-hao,SONG Li-ping,XIAO Xuan   

  1. Jingdezhen Ceramic Institute,Jingdezhen,Jiangxi 333001,China
  • Received:2008-11-16 Revised:2009-02-09 Online:2010-05-21 Published:2010-05-21
  • Contact: HU Hong-hao

摘要: 蛋白质结构预测是后基因组时代的一项重要任务,蛋白质二级结构预测是蛋白质结构预测的关键步骤。利用氨基酸数字编码模型生成蛋白质序列的元胞自动机图(Cellular Automata Image,CAI),提出了一种基于灰度共生矩阵(Gray Level Co-occurrence Matrix,GLCM)提取纹理图像特征的方法。用扩大的协方差算法进行预测,仿真结果显示有较好的分类效果,Jackknife检验的预测成功率达到94.61%。

Abstract: One of the important tasks of the post genome project is protein structure prediction,the key step of which is protein secondary structure prediction.This paper makes use of a model of digital coding for amino acid,and uses cellular automata to generate image representation for protein sequences.A protein sequence can be represented by a unique image,and the image takes into account the interactional actions between amino acids.By the Gray Level Co-occurrence Matrix(GLCM) deriving from the CAI,a novel method has been developed that can be used to predict the secondary structure of the protein.The result thus obtained is quite promising.

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