title: Classification analysis of dual nucleotides using dimension reduction.
abstract: We introduce a new approach to investigate the dual nucleotides compositions of 11 Gram-positive and 12 Gram-negative eubacteria recently studied by Sorimachi and Okayasu. The approach firstly obtains a 16-dimension vector set of dual nucleotides by PN-curve from the complete genome of organism. Each vector of the set corresponds to a single gene of genome. Then we reduce the 16-dimension vector set to 2-dimension by principal components analysis (PCA). The reduction avoids possible loss of information averaging all 16-dimension vectors. Then we suggest a 2D graphical representation based on the 2-dimension vector to investigate the classification patters among different organisms.
authors.affiliation: Shijiazhuang Railway Institute, Hebei, People's Republic of China. zhqi_yh2004@yahoo.com.cn
authors.forename: Zhao-Hui
authors.initials: ZH
authors.lastname: Qi
authors.forename: Jian-Min
authors.initials: JM
authors.lastname: Wang
authors.forename: Xiao-Qin
authors.initials: XQ
authors.lastname: Qi
mesh_terms: D004269:DNA, Bacterial / Q000235:genetics*; D016680:Genome, Bacterial; D006090:Gram-Negative Bacteria / Q000145:classification / Q000235:genetics*; D006094:Gram-Positive Bacteria / Q000145:classification / Q000235:genetics*; D025341:Principal Component Analysis
chemical_list: D004269:DNA, Bacterial