超二级结构

用离散量的方法识别蛋白质的超二级结构

The protein super-secondary structure recognition with the method of diversity measure

每个超二级结构序列表达成一个36维的特征向量，用作分类器的输入。

Each supersecondary structural motif is represented as a feature vector of 36 dimensions , which is used as input of classifier .

首次将二次判别分析方法用于一般超二级结构的预测。

The method of increment of diversity combined with quadratic discriminant analysis , for the first time , is used to predict supersecondary structural motifs .

用离散量的方法，对2208个分辨率在2.5I以上的高精度的蛋白质结构中四类超二级结构进行了识别。

Four types of super-secondary structures of the 2208 proteins with higher resolution ( > 2.5A ) were predicted by using of the diversity increment algorithm .

用离散量及离散增量表达一般超二级结构序列的表征信息。用氨基酸基本组成成份，二肽成份以及氨基酸组成分布三种方式表达一般超二级结构特征。

Measure of diversity and increment of diversity are used to represent the feature information of protein sequential pattern . Amino acid basic compositions , dipeptide components and amino acid composition distribution are combined to represent the compositional features .