首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于氨基酸分子中侧链基极性性质的DNA序列分类(英文)
引用本文:王显金.基于氨基酸分子中侧链基极性性质的DNA序列分类(英文)[J].农业科学与技术,2014(5):751-755.
作者姓名:王显金
作者单位:宁波大红鹰学院,浙江宁波315175
基金项目:浙江省自然科学基金项目(LY13A010007).
摘    要:从DNA序列片段个案中密码子分布密度角度出发,提取出DNA序列片段的特征,基于氨基酸分子中侧链基极性性质把氨基酸分成5大类,计算5大类出现的频率,这种考虑生物意义的特征提取方法不仅考虑碱基的含量,还在一定程度上考虑碱基的排列顺序,应用层次聚类分析方法和BP神经网络法对DNA序列片段进行分类。结果表明,2类算法分类结果精度较高,且一致性也较高。说明这种特征提取法比传统的单纯考虑碱基的特征提取法效果更优。

关 键 词:密码子  频率  层次聚类分析  BP神经网络法

DNA Sequence Classification Based on the Side Chain Radical Polarity of Amino Acids
Xianjin WANG.DNA Sequence Classification Based on the Side Chain Radical Polarity of Amino Acids[J].Agricultural Science & Technology,2014(5):751-755.
Authors:Xianjin WANG
Institution:Xianjin WANG( Ningbo Dahongying University, Ningbo 315175, China)
Abstract:The features of DNA sequence fragments were extracted from the distribution density of the condons in the individual cases of DNA sequence fragments. Based on the polarity of side chain radicals of amino acids molecules, the amino acids were classified into five categories, and the frequencies of these five categories were calculated. This kind of feature extraction based on the biological meanings not only took the content of basic groups into consideration, but also considered the marshal ing sequence of the basic groups. The hierarchical clustering analysis and BP neural network were used to classify the DNA sequence fragments. The results showed that the classification results of these two kinds of algo-rithms not only had high accuracy, but also had high consistence, indicating that this kind of feature extraction was superior over the traditional feature extraction which only took the features of basic groups into consideration.
Keywords:Codon  Frequency  Hierarchical clustering analysis  BP neural network
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号