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

Ping, Pengyao; Zhu, Xianyou; Wang, Lei

doi:10.1142/s0218339017500024

Cited by 15 publications

(9 citation statements)

References 23 publications

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“…For example, gure-6 and gure-7 show the phylogenetic trees of ND4 protein sequence obtained by the use of complex representation of Amino Acids under Hydrophobicity & Residue Volumes and Hydrophilicity & Residue Volume respectively as found in [34].It re ects the exact relationship of the species as obtained by the present method. Again, Figure -8 shows the phylogenetic tree of the 16 ND5 protein sequences based on the PCA-FFT analysis [35]. Comparing this with Fig.…”

Section: Resultsmentioning

confidence: 93%

Selection of Moment Vectors in Protein Sequence Comparison Under Binary Representation

Pal¹,

Ghosh²,

Maji

et al. 2021

Preprint

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Similarity/dissimilarity study of protein and genome sequences remains a challenging task and selection of techniques and descriptors to be adopted, plays an important role in computational biology. Again, genome sequence comparison is always preferred to protein sequence comparison due the presence of 20 amino acids in protein sequence compared to only 4 nucleotides in genome sequence. So it is important to consider suitable representation that is both time and space efficient and also equally applicable to protein sequences of equal and unequal lengths. In the binary form of representation, Fourier transform of a protein sequence reduces to the transformation of 20 simple binary sequences in Fourier domain, where in each such sequence, Perseval’s Identity gives a very simple computable form of power spectrum. This gives rise to readily acceptable forms of moments of different degrees. Again such moments, when properly normalized, show a monotonically descending trend with the increase in the degrees of the moments. So it is better to stick to moments of smaller degrees only. In this paper, descriptors are taken as 20 component vectors, where each component corresponds to a general second order moment of one of the 20 simple binary sequences. Then distance matrices are obtained by using Euclidean distance as the distance measure between each pair of sequence. Phylogenetic trees are obtained from the distance matrices using UPGMA algorithm. In the present paper, the datasets used for similarity/dissimilarity study are 9 ND4, 16 ND5, 9 ND6, 24 TF proteins and 12 Baculovirus proteins. It is found that the phylogenetic trees produced by the present method are at par with those produced by the earlier methods adopted by other authors and also their known biological references. Further it takes less computational time and also it is equally applicable to sequences of equal and unequal lengths.

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Section: Resultsmentioning

confidence: 93%

Selection of Moment Vectors in Protein Sequence Comparison Under Binary Representation

Pal¹,

Ghosh²,

Maji

et al. 2021

Preprint

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show abstract

“…It is colored red. Despite the wrong classification of MHVJHM virus, our approach corrects the broken classification of Class I in [26]. According to the results in Tables 9, 10, and 11, the angle is preferred to be used as shown in Figures 1, 2, and 3.…”

Section: Similarity/dissimilarity Analysismentioning

confidence: 92%

“…The others are severe acute respiratory syndrome coronaviruses (SARS-CoV). This sample set is applied before in [26].…”

Section: Dataset Technology and Toolsmentioning

confidence: 99%

A Statistical Similarity/Dissimilarity Analysis of Protein Sequences Based on a Novel Group Representative Vector

Elwahaab

Abo-Elkhier

Maaty

2019

BioMed Research International

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Similarity/dissimilarity analysis is a key way of understanding the biology of an organism by knowing the origin of the new genes/sequences. Sequence data are grouped in terms of biological relationships. The number of sequences related to any group is susceptible to be increased every day. All the present alignment-free methods approve the utility of their approaches by producing a similarity/dissimilarity matrix. Although this matrix is clear, it measures the degree of similarity among sequences individually. In our work, a representative of each of three groups of protein sequences is introduced. A similarity/dissimilarity vector is evaluated instead of the ordinary similarity/dissimilarity matrix based on the group representative. The approach is applied on three selected groups of protein sequences: beta globin, NADH dehydrogenase subunit 5 (ND5), and spike protein sequences. A cross-grouping comparison is produced to ensure the singularity of each group. A qualitative comparison between our approach, previous articles, and the phylogenetic tree of these protein sequences proved the utility of our approach.

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“…A 2D graphical representation of protein sequences based on six physicochemical properties of amino acids is outlined [21]. The properties are Mr a , pI a , Solubilityb [g/100g, 25 0 C], Specific rotation [α] D 25 , (5N HCl) c , Hydropathy index d , Melting point c (°C). The numerical characterization of protein graphs is given as the descriptor.…”

mentioning

confidence: 99%

“…By correlation analysis, the ClustalW results are compared with the present results and other graphical representation results to demonstrate the effectiveness of this approach. A novel method to analyze the similarity/dissimilarity of protein sequences based on Principal Component Analysis-Fast Fourier Transformation (PCA-FFT) is proposed [25]. The nine different physio-chemical properties of amino acids considered in the analysis are mW, hI, pk1, pK2, pI, S, cN, F(%) and vR.…”

mentioning

confidence: 99%

A Critical Mathematical Review on Protein Sequence Comparison Using Physio-Chemical Properties of Amino Acids

2020

J Mol Genet

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

Cited by 15 publications

References 23 publications

Selection of Moment Vectors in Protein Sequence Comparison Under Binary Representation

Selection of Moment Vectors in Protein Sequence Comparison Under Binary Representation

A Statistical Similarity/Dissimilarity Analysis of Protein Sequences Based on a Novel Group Representative Vector

A Critical Mathematical Review on Protein Sequence Comparison Using Physio-Chemical Properties of Amino Acids

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