An efficient numerical method for protein sequences similarity analysis based on a new two-dimensional graphical representation

El-Lakkani, Ali; Mahran, Hesham Galal

doi:10.1080/1062936x.2014.995700

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…Thus, a protein sequence can be characterized by a 17-D vector containing the frequencies of the amplitudes. Based on the idea of cyclic order of 20 AAs, Ellakkani and Mahran (2015) selected twenty concentric evenly spaced circles divided by n radial lines into equal divisions to represent any protein sequence of length n . The mean of each two successive distances between each two successive AAs was calculated.…”

Section: Introductionmentioning

confidence: 99%

A novel model for protein sequence similarity analysis based on spectral radius

Gao

Marinis

et al. 2018

Journal of Theoretical Biology

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Advances in sequencing technologies led to rapid increase in the number and diversity of biological sequences, which facilitated development in the sequence research. In this paper, we present a new method for analyzing protein sequence similarity. We calculated the spectral radii of 20 amino acids (AAs) and put forward a novel 2-D graphical representation of protein sequences. To characterize protein sequences numerically, three groups of features were extracted and related to statistical, dynamics measurements and fluctuation complexity of the sequences. With the obtained feature vector, two models utilizing Gaussian Kernel similarity and Cosine similarity were built to measure the similarity between sequences. We applied our method to analyze the similarities/dissimilarities of four data sets. Both proposed models received consistent results with improvements when compared to that obtained by the ClustalW analysis. The novel approach we present in this study may therefore benefit protein research in medical and scientific fields.

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Section: Introductionmentioning

confidence: 99%

A novel model for protein sequence similarity analysis based on spectral radius

Gao

Marinis

et al. 2018

Journal of Theoretical Biology

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“…El-Lakkani and Mahran introduce a two dimensional graphical representation of protein sequences. They propose a new mathematical descriptor in their paper to measure the similarity of two protein sequences [28]. Li et al present a graphical representation with the name of UC-Curve [29].…”

Section: Introductionmentioning

confidence: 99%

A new method to analyze protein sequence similarity using Dynamic Time Warping

Hou

Pan

Peng³

et al. 2017

Genomics

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Sequences similarity analysis is one of the major topics in bioinformatics. It helps researchers to reveal evolution relationships of different species. In this paper, we outline a new method to analyze the similarity of proteins by Discrete Fourier Transform (DFT) and Dynamic Time Warping (DTW). The original symbol sequences are converted to numerical sequences according to their physico-chemical properties. We obtain the power spectra of sequences from DFT and extend the spectra to the same length to calculate the distance between different sequences by DTW. Our method is tested in different datasets and the results are compared with that of other software algorithms. In the comparison we find our scheme could amend some wrong classifications appear in other software. The comparison shows our approach is reasonable and effective.

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“…On the other hand, ClustalW also correctly separates the proteins into their correct groups (Fig.7). Yao et al [18] Ellakani and Mahran [27] Zhang et al [15] Mu et al [28] Liu et al [29] Wu et al […”

Section: Similarity Analysis Of Coronavirus Spike Proteinsmentioning

confidence: 99%

An alignment-free method for bulk comparison of protein sequences from different species

Doğan

2019

Balkan Journal of Electrical and Computer Engineering

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The available number of protein sequences rapidly increased with the development of new sequencing techniques. This in turn led to an urgent need for the development of new computational methods utilizing these data for the solution of different biological problems. One of these problems is the comparison of protein sequences from different species to reveal their evolutional relationship. Recently, several alignment-free methods have been proposed for this purpose. Here in this study, we also proposed an alignment-free method for the same purpose. Different from the existing methods, the proposed method not only allows for a pairwise comparison of two protein sequences, but also it allows for a bulk comparison of multiple protein sequences simultaneously. Computational results performed on gold-standard datasets showed that, bulk comparison of multiple sequences is much faster than its pairwise counterpart and the proposed method achieves a performance which is quite competitive with the state-of-the-art alignmentbased method, ClustalW.

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An efficient numerical method for protein sequences similarity analysis based on a new two-dimensional graphical representation

Cited by 8 publications

References 28 publications

A novel model for protein sequence similarity analysis based on spectral radius

A novel model for protein sequence similarity analysis based on spectral radius

A new method to analyze protein sequence similarity using Dynamic Time Warping

An alignment-free method for bulk comparison of protein sequences from different species

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