Classification analysis of dual nucleotides using dimension reduction

JOURNAL OF THEORETICAL BIOLOGY

卷:260

Article

Qi, Zhao-Hui¹  Wang, Jian-Min¹  Qi, Xiao-Qin¹ 

[1] Shijiazhuang Railway Inst, Sch Comp & Informat Engn, Shijiazhuang 050043, Hebei, Peoples R China

关键词: Dual nucleotides compositions;    Principal components analysis (PCA);    Graphic representation;    Genome;    Eubacteria;   

DOI  :  10.1016/j.jtbi.2009.05.011

来源: Elsevier

【 摘 要 】

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. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.

【 授权许可】

Free