Bilateral similarity function: A novel and universal method for similarity analysis of biological sequences

Wang, Shiyuan; Tian, Fengchun; Qiu, Yongjun; Liu, Xiao

doi:10.1016/j.jtbi.2010.04.013

Cited by 19 publications

(16 citation statements)

References 58 publications

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“…On the other hand, we found that the difference of ND5 protein between specie (9) and other species are greatest. In addition, the results obtained from numerical experiments are consistent with the fact of biological evolution [11,12], which also demonstrates the effectiveness of this method to some extent.…”

Section: Resultssupporting

confidence: 75%

A Novel Method for Similarity Analysis of Protein Sequences

Liu¹,

Zhao²,

Liu³

2015

Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering

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Abstract. A new method for similarity analysis of protein sequences is presented in this paper. On the basis of positions, proportion difference and various physicochemical properties of 20 kinds of amino acid in different protein sequences, representative information was extracted from protein sequence and converted into a numeric vector, thus further similarities of protein sequences were analyzed by studying the similarities between vectors. To facilitate the comparison between protein sequences of different length, every protein sequence is first mapped to a fixed-length vector, of which the vector information is relative position of amino acids. Then percentage of 20 kinds of amino acids in the sequence and 3 physicochemical properties are combined to constitute physicochemical information vector. Finally, a one-dimensional feature vector with 80 elements(feature vector) representing a protein sequence is synthesized. The shortest distance method was applied for cluster analysis on feature vectors so as to analyze similarities in protein sequences. In the numerical experiment part of the article, similarity analysis was conducted for 9 different species of the mitochondrial NADH dehydrogenase. The result of numerical experiment is consistent with the biological fact, which validates the effectiveness of model to a certain extent.

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Section: Resultssupporting

confidence: 75%

A Novel Method for Similarity Analysis of Protein Sequences

Liu¹,

Zhao²,

Liu³

2015

Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering

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“…For comparison, we list the recently published results of the examination of the degree of similarity between Human and other several species in Fig. 8 (Zhang, 2009;Yu et al, 2009;Wang et al, 2010;Xie and Mo, 2011). As one can see there is an overall agreement among similarities obtained by different approaches despite some variation among them.…”

Section: Sequence Comparison With Polar Representationmentioning

confidence: 97%

Sequence comparison via polar coordinates representation and curve tree

Dai

Guo

2012

Journal of Theoretical Biology

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Sequence comparison has become one of the essential bioinformatics tools in bioinformatics research, which could serve as evidence of structural and functional conservation, as well as of evolutionary relations among the sequences. Existing graphical representation methods have achieved promising results in sequence comparison, but there are some design challenges with the graphical representations and feature-based measures. We reported here a new method for sequence comparison. It considers whole distribution of dual bases and employs polar coordinates method to map a biological sequence into a closed curve. The curve tree was then constructed to numerically characterize the closed curve of biological sequences, and further compared biological sequences by evaluating the distance of the curve tree of the query sequence matching against a corresponding curve tree of the template sequence. The proposed method was tested by phylogenetic analysis, and its performance was further compared with alignment-based methods. The results demonstrate that using polar coordinates representation and curve tree to compare sequences is more efficient.

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“…Most of the existing methods for similarity identification are based on some kind of graphical representation (Randiü et al, 2003;Liao and Wang, 2004;Wang et al, 2010).…”

Section: Similarity Evaluation Derived From Cgrmentioning

confidence: 99%

“…They also create the possibility of numerical characterization to obtain a quantitative measure of the degree of similarity/dissimilarity of different DNA/protein sequences (Deschavanne et al, 1999;Randiü et al, 2003;Liao and Wang, 2004;Wang et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Similarity analysis for DNA sequences based on chaos game representation. Case study: The albumin

Stan

Cristescu

Scarlat

2010

Journal of Theoretical Biology

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Bilateral similarity function: A novel and universal method for similarity analysis of biological sequences

Cited by 19 publications

References 58 publications

A Novel Method for Similarity Analysis of Protein Sequences

A Novel Method for Similarity Analysis of Protein Sequences

Sequence comparison via polar coordinates representation and curve tree

Similarity analysis for DNA sequences based on chaos game representation. Case study: The albumin

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