Further analysis and study based on a visualized method for SARS RNA sequences
Liu, G.; Yang, J.; Xu, Z.; Wang, M.; Huang, Z.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 24(1): 26-31
2007
ISSN/ISBN: 1001-5515 PMID: 17333886 Document Number: 610642
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.