title: [A new method for visual SARS DNA sequences analysis].
abstract: 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.
authors.affiliation: Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China.
authors.forename: Zhijie
authors.initials: Z
authors.lastname: Xu
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Guoping
authors.initials: G
authors.lastname: Liu
authors.forename: Meng
authors.initials: M
authors.lastname: Wang
authors.forename: Zhende
authors.initials: Z
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D045473:Severe acute respiratory syndrome-related coronavirus / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*