2-D graphical representation of protein sequences and its application to coronavirus phylogeny

Li, Chun; Xing, Lili; Wang, Xin

doi:10.5483/bmbrep.2008.41.3.217

Cited by 38 publications

(41 citation statements)

References 40 publications

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“…Afterwards, more graphical representations of DNA sequences were well developed by researchers [1,2,[6][7][8][9][10][11][12][13][14][15]. In comparison with DNA, graphical representations of proteins emerged only very recently [2,[16][17][18][19][20][21][22][23][24][25][26][27]. As a matter of fact, most of the graphical representations of DNA involve some degree of arbitrariness, such as the selection of directions to be assigned to individual bases.…”

Section: Introductionmentioning

confidence: 99%

“…It is impracticable to represent one protein sequence by such an enormous number of graphs. This is probably the most important reason why protein graphical representations have not been advanced [19,23]. It is found that reducing the alphabet or fixing the directions assigned to amino acid residues plays an important role in addressing this problem.…”

Section: Introductionmentioning

confidence: 99%

“…It is found that reducing the alphabet or fixing the directions assigned to amino acid residues plays an important role in addressing this problem. For details, we refer to some recent publications [2,16,21,23,24,28].…”

Section: Introductionmentioning

confidence: 99%

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Numerical Characterization of Protein Sequences Based on the Generalized Chou’s Pseudo Amino Acid Composition

Lin

2016

Applied Sciences

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Abstract:The technique of comparison and analysis of biological sequences is playing an increasingly important role in the field of Computational Biology and Bioinformatics. One of the key steps in developing the technique is to identify an appropriate manner to represent a biological sequence. In this paper, on the basis of three physical-chemical properties of amino acids, a protein primary sequence is reduced into a six-letter sequence, and then a set of elements which reflect the global and local sequence-order information is extracted. Combining these elements with the frequencies of 20 native amino acids, a (21 + λ) dimensional vector is constructed to characterize the protein sequence. The utility of the proposed approach is illustrated by phylogenetic analysis and identification of DNA-binding proteins.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical Characterization of Protein Sequences Based on the Generalized Chou’s Pseudo Amino Acid Composition

Lin

2016

Applied Sciences

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“…For a given graph, one can transform it into another mathematical object, a matrix. The matrices associated with a graph include ED, D/D, L/L, and their 'higher order' matrices [ Refs 18,[20][21][22][23][29][30][31][32]. Among them, L/L is a matrix whose elements are defined as the quotient of the Euclidean distance between a pair of vertices (dots) of the zigzag curve and the sum of distances between the same pair of vertices measured along the zigzag curve.…”

Section: E the Ale-index Based Algorithm To Examine Similarities Of mentioning

confidence: 99%

An ALE-Index Based Algorithm Facilitated Prediction of Success for Polymerase Chain Reactions

Zhang

et al. 2009

2009 3rd International Conference on Bioinformatics and Biomedical Engineering

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Polymerase chain reaction (PCR), though invented over twenty years ago and having been developed with much advance, still face challenges nowadays. Long DNA and most high GC content DNA sequences are still hard to amplify. People have had few tools to predict whether a PCR is successful or not before a real PCR experiment is done. In this study, 189 randomly selected short amplicons from human genome were represented as "four horizontal lines" DNA graphs followed by ALE-index based algorithm to compare relative similarities among each other, and were classified as two groups, which basically coincided with the real experimental results in which these amplicons were divided into successful and unsuccessful groups. The accuracy of the algorithm was about 91%.

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“…Because the number of types of amino acids in a protein sequence is much greater than the number of types of bases in a DNA sequence, it is difficult to directly generalize the graphical representation of a DNA sequence to that of a protein sequence [4][5][6]. One method is to classify 20 amino acids into four or five classes, and simplify the protein sequence to a sequence of four or five characters, and then use the graphical method of DNA sequences to describe the simplified protein sequence [7][8][9][10]. Another method is to ignore the similarities and differences for all amino acids and arrange them in lexicographical order directly from the sequence.…”

Section: Introductionmentioning

confidence: 99%

Primary structure similarity analysis of proteins sequences by a new graphical representation

Xu¹,

Li²,

Zhang³

et al. 2014

SAR and QSAR in Environmental Research

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A new graphical description of the primary structure of protein sequences is introduced. First, a three-dimensional space discrete point set of a protein sequence is created based on the three main physicochemical properties of the amino acids. Secondly, a continuous cubic B-spline curve interpolating the amino acid points is constructed to represent the shape of the protein sequence. Then the geometric properties (curvature and torsion) of the continuous curve are extracted for the purpose of analyzing the similarity between protein sequences. Finally, an improved Canberra distance comparison is introduced for the similarity analysis of protein sequences with different lengths. Experimental results show that our method is effective for the similarity comparison of protein sequences.

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2-D graphical representation of protein sequences and its application to coronavirus phylogeny

Cited by 38 publications

References 40 publications

Numerical Characterization of Protein Sequences Based on the Generalized Chou’s Pseudo Amino Acid Composition

Numerical Characterization of Protein Sequences Based on the Generalized Chou’s Pseudo Amino Acid Composition

An ALE-Index Based Algorithm Facilitated Prediction of Success for Polymerase Chain Reactions

Primary structure similarity analysis of proteins sequences by a new graphical representation

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