Classification analysis of dual nucleotides using dimension reduction

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. Eac...

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Detalles Bibliográficos
Autores principales: Qi, Zhao-Hui, Wang, Jian-Min, Qi, Xiao-Qin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Ltd. 2009
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126582/
https://www.ncbi.nlm.nih.gov/pubmed/19481099
http://dx.doi.org/10.1016/j.jtbi.2009.05.011
Descripción
Sumario: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.

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