title: [Further analysis and study based on a visualized method for SARS RNA sequences].
abstract: This paper proposed a new kind of visualized method of genome. Using cellular automation theory, the visual method transfers one-dimensional RNA sequence into two-demension visual image. Applying this method to SARS RNA sequence analysis, the characteristic of SARS-CoV differing from Non-SARS is discovered. This paper extracts characteristic genome fragment, visualize them, and study them with some pattern recognition method such as PCA and SVM. The result shows that the characteristic of SARS-CoV is classifiable. Some combined methods can use the characteristic more sufficient as an un-routine method.
authors.affiliation: Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China. ahphone@sjtu.edu.cn
authors.forename: Guoping
authors.initials: G
authors.lastname: Liu
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Zhijie
authors.initials: Z
authors.lastname: Xu
authors.forename: Meng
authors.initials: M
authors.lastname: Wang
authors.forename: Zhende
authors.initials: Z
authors.lastname: Huang
mesh_terms: D016679:Genome, Viral; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012367:RNA, Viral / Q000235:genetics*; D045473:Severe acute respiratory syndrome-related coronavirus / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D012367:RNA, Viral