基于生物信息学的功能蛋白基因序列分类研究

Bioinformatics sciences most important duty is to withdraw the valuable knowledge from the massive biology information data. Scientists carry on the comparison with the unknown function sequences and the known function sequences to predict the function of sequences of unknown function, is a common means to explore knowledge in the bioinformatics. We use BLAST algorithm to alignment sequences that the gene sequences of plant virus-encoded movement proteins and coat proteins in this paper, then use principal component analysis to extract five feature vectors based the results of the distance matrix which we get after sequences alignment, and finally use Support Vector Machines to build classification model for the two types of proteins gene sequencing categorize and validate the results of classification model, the correct recognition rate and rejection rate of the classification model can reach 80% or higher, this methods are more suitable for the classification of the two tapes proteins.