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.
Subject(s)
Genome, Viral , Image Processing, Computer-Assisted , Methods , RNA, Viral , Genetics , Severe acute respiratory syndrome-related coronavirus , Genetics , Sequence Analysis, RNA , MethodsABSTRACT
Traditional DNA sequence analysis is based on sequence alignment, while a new DNA visual sequence analysis is proposed in this paper. Based on S. Wolfram's cellular automation theory, the method transfers one-dimensional DNA sequence into two-demensional visual image. Applying this method to SARS DNA sequence analysis, a characteristic of SARS-CoV differing from non-SARS is discovered. Compared with all known coronaviruses' images, It is found that this is a unique characteristic of SARS virus, and it is helpful to clinical identification of SARS.