There are multi -scale feature gene expression, the maximum classification rate is 98.61%, with stable results.
基因表达具有明显的多尺度特征，分类率最大达到98.61%，结果稳定。
The features of gene expression are extracted by the wavelet multi-resolution analysis, the features are classified by the support vector machines and BP neural network methods.
采用小波多分辩率分析方法提取基因表达的特征，利用支持向量机和BP神经网络方法进行分类。
Objective to construct an eukaryotic expression vector of compound multi-epitope gene of HCV and express the gene in COS7 cells.
目的建立丙型肝炎病毒(HCV)复合多表位基因的真核表达载体，并在COS7细胞中瞬时表达。
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