Analysis of similarity/dissimilarity of protein sequences

Yao, Yao; Dai, Qi; Chun, Li; He, Ping‐an; Nan, Xuying; Zhang, Yaozhou

doi:10.1002/prot.22110

Cited by 70 publications

(52 citation statements)

References 36 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: 73%

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: 73%

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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“…If the points are all around the trend line, this shows that the correlation is better. Observing the figure, our method presented higher correlation with Clustal W than the methods of Hou et al, 5 Elmaatv et al, 6 Wen et al method, 7 Zhang et al method, 8 Wu et al, 9 Yao et al, 10 and He et al 14 …”

mentioning

confidence: 66%

“…Wu et al 9 proposed a two-dimensional graph, called "2D-MH" to compare the evolutionary distances between any number of protein sequences. Yao et al 10 introduced a dynamic 2D graphical representation based on physicochemical properties of amino acids and compared the sequences of nine ND5 proteins. Mu et al 11 compared the similarity/dissimilarity of protein sequences according to the distance frequency of amino acids.…”

Section: Introductionmentioning

confidence: 99%

Similarities/Dissimilarities Analysis of Protein Sequences Based on Pca-FFT

2017

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In this paper, a novel method to analyze the similarity/dissimilarity of protein sequences based on Principal Component Analysis-Fast Fourier Transformation (PCA-FFT) is proposed, in which, the PCA is utilized to transform protein sequences into time series and the FFT is utilized to analyze the time series while considering them as signals. To test the effectiveness of our newly proposed method, it is applied to analyze the similarity/dissimilarity of 16 different ND5 protein sequences and 29 different spike protein sequences, respectively. Furthermore, the correlation analysis is presented for comparing with others methods, and the simulation results show that it has better performances in the aspects of computation complexity and recognition degree than some existing methods.

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“…For large proteins, it is not a visual representation and is not directly related to similarity of sequences. Yao et al [22] introduced a dynamic 2D graphical representation of protein sequences based on the pKa values used by Randić. This dynamic approach can help us to inspect the data and recognize the major similarities among different proteins.…”

Section: Introductionmentioning

confidence: 99%

A novel 2D graphical representation of protein sequence based on individual amino acid

Sun

Wang

2010

Int J of Quantum Chemistry

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The primary structure, i.e., the amino acids sequence, plays determinant roles in dynamical folding process and stable structure of protein molecules, then how to put forward sequences based approaches to demonstrate the biological information of the primary sequence will facilitate correlative researches. In this article, we outline a novel 2D graphical representation on the basis of a selected pair of physiochemical properties of amino acids, which integrates both the electric and hydrophobic factors to demonstrate the characteristic features of proteins. This novel representation transforms protein into a zigzag curve uniquely and allows direct inspection of similarities/dissimilarities among different protein sequences with higher resolution than previous methods. From this representation, some efficient numerical descriptors are derived, by which we quantitatively analyze the evolutionary distances among the ND6 (NADH dehydrogenase subunit 6) protein sequences of eight species, the results are coincident with the actual evolutions, which illustrate the efficiencies of the present approach. This representation can also provide convenient tools and alternative studying strategies for protein sequences and structures analysis.

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Analysis of similarity/dissimilarity of protein sequences

Cited by 70 publications

References 36 publications

A Novel Method for Similarity Analysis of Protein Sequences

A Novel Method for Similarity Analysis of Protein Sequences

Similarities/Dissimilarities Analysis of Protein Sequences Based on Pca-FFT

A novel 2D graphical representation of protein sequence based on individual amino acid

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