Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0167430
Title: An alignment-free algorithm in comparing the similarity of protein sequences based on Pseudo-Markov transition probabilities among amino acids
Authors: Li Y.
Song T.
Yang J. 
Zhang Y.
Yang J.
Keywords: amino acid
glycosidase
xylan endo 1,3 beta xylosidase
amino acid
protein
accuracy
algorithm
alignment free algorithm
amino acid sequence
Article
correlation coefficient
human
nonhuman
phylogenetic tree
probability
thermostability
algorithm
amino acid sequence
chemistry
procedures
sequence alignment
sequence analysis
Algorithms
Amino Acid Sequence
Amino Acids
Glycoside Hydrolases
Probability
Proteins
Sequence Alignment
Sequence Analysis, Protein
Issue Date: 2016
Citation: Li Y., Song T., Yang J., Zhang Y., Yang J. (2016). An alignment-free algorithm in comparing the similarity of protein sequences based on Pseudo-Markov transition probabilities among amino acids. PLoS ONE 11 (12) : e0167430. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0167430
Abstract: In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the sequence. By evaluating the Euclidean distances among the representing vectors, we compare the similarity of protein sequences. We then apply this method into the ND5 dataset consisting of the ND5 protein sequences of 9 species, and the F10 and G11 datasets representing two of the xylanases containing glycoside hydrolase families, i.e., families 10 and 11. As a result, our method achieves a correlation coefficient of 0.962 with the canonical protein sequence aligner ClustalW in the ND5 dataset, much higher than those of other 5 popular alignment-free methods. In addition, we successfully separate the xylanases sequences in the F10 family and the G11 family and illustrate that the F10 family is more heat stable than the G11 family, consistent with a few previous studies. Moreover, we prove mathematically an identity equation involving the Pseudo-Markov transition probability vector and the amino acids content ratio vector. © 2016 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161540
ISSN: 19326203
DOI: 10.1371/journal.pone.0167430
Appears in Collections:Staff Publications
Elements

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1371_journal_pone_0167430.pdf1.39 MBAdobe PDF

OPEN

NoneView/Download

SCOPUSTM   
Citations

5
checked on Sep 13, 2020

Page view(s)

83
checked on Sep 18, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.