Phylogenetic Analysis: A Novel Method of Protein Sequence Similarity Analysis

Author:

Li Wei1ORCID,Yang Lina1,Meng Zuqiang1,Qiu Yu1,Wang Patrick Shen-Pei2,Li Xichun3

Affiliation:

1. School of Computer, Electronics and Information, Guangxi University, Nanning, P. R. China

2. Computer and Information Science, Northeastern University, Boston, MA 02115, USA

3. Guangxi Normal University for Nationalities, Chongzuo 532200, China

Abstract

Protein sequence similarity analysis (PSSA) is a significant task in bioinformatics, which can obtain information about unknown sequences such as protein structures and homology relationships. Protein sequence refers to the series of amino acids with rich physical and chemical properties, namely the basic structure of proteins. However, sequence similarity analysis and phylogenetic analysis between different species which have complex amino acid sequences is a challenging problem. In this paper, nine properties of amino acids were considered and the sequence was converted into numerical values by principal component analysis (PCA); with Haar Wavelet Transform, and Higuchi fractal dimension (HFD), a new feature vector is constructed to represent the sequence; Spearman distance was selected to calculate the distance matrix and the phylogenetic tree was constructed. In this paper, two representative protein sequences (9 ND5 (NADH dehydrogenase 5) and 8 ND6 (NADH dehydrogenase 6)) were selected for similarity analysis and phylogenetic analysis, and compared with MEGA software and other existing methods. The extensive results show that our method is outperforming and results consistent with the known facts.

Funder

National Natural Science Foundation of China

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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