Alignment-free method for DNA sequence clustering using Fuzzy integral similarity

Saw, Ajay Kumar; Raj, Garima; Das, Manashi; Talukdar, Narayan Chandra; Tripathy, Binod Chandra; Nandi, Soumyadeep

doi:10.1038/s41598-019-40452-6

Cited by 21 publications

(9 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, Zhou et al constructed a complex network for similarity/dissimilarity analysis of DNA sequences [ 1 ]. Saw et al perform DNA sequence comparison using the fuzzy integral with Markov chain [ 2 ]. Lichtblau uses Frequency Chaos Game Representation and signal processing for genomic sequence comparison [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Non-standard bioinformatics characterization of SARS-CoV-2

Bielińska-Wąż

Wąż

2021

Computers in Biology and Medicine

View full text Add to dashboard Cite

A non-standard bioinformatics method, 4D-Dynamic Representation of DNA/RNA Sequences , aiming at an analysis of the information available in nucleotide databases, has been formulated. The sequences are represented by sets of “material points” in a 4D space - 4D-dynamic graphs. The graphs representing the sequences are treated as “rigid bodies” and characterized by values analogous to the ones used in the classical dynamics. As the graphical representations of the sequences, the projections of the graphs into 2D and 3D spaces are used. The method has been applied to an analysis of the complete genome sequences of the 2019 novel coronavirus. As a result, 2D and 3D classification maps are obtained. The coordinate axes in the maps correspond to the values derived from the exact formulas characterizing the graphs: the coordinates of the centers of mass and the 4D moments of inertia. The points in the maps represent sequences and their coordinates are used as the classifiers. The main result of this work has been derived from the 3D classification maps. The distribution of clusters of points which emerged in these maps, supports the hypothesis that SARS-CoV-2 may have originated in bat and in pangolin. Pilot calculations for Zika virus sequence data prove that the proposed approach is also applicable to a description of time evolution of genome sequences of viruses.

show abstract

Section: Introductionmentioning

confidence: 99%

Non-standard bioinformatics characterization of SARS-CoV-2

Bielińska-Wąż

Wąż

2021

Computers in Biology and Medicine

View full text Add to dashboard Cite

show abstract

“…We represented the protein sequence as a set of material points in a 20D space [14]. Saw et al analyzed the similarity of DNA sequences using the fuzzy integral with a Markov chain [15]. Lichtblau applied frequency chaos game representation and signal processing for genomic sequence comparison [16].…”

Section: G G T T G G a A 2 G T G T G A G Amentioning

confidence: 99%

4D-Dynamic Representation of DNA/RNA Sequences: Studies on Genetic Diversity of Echinococcus multilocularis in Red Foxes in Poland

Bielińska-Wąż

Wąż

Lass

et al. 2022

Life

View full text Add to dashboard Cite

The 4D-Dynamic Representation of DNA/RNA Sequences, an alignment-free bioinformatics method recently developed by us, has been used to study the genetic diversity of Echinococcus multilocularis in red foxes in Poland. Sequences of three mitochondrial genes, i.e., NADH dehydrogenase subunit 2 (nad2), cytochrome b (cob), and cytochrome c oxidase subunit 1 (cox1), are analyzed. The sequences are represented by sets of material points in a 4D space, i.e., 4D-dynamic graphs. As a visualization of the sequences, projections of the graphs into 3D space are shown. The differences between 3D graphs corresponding to European, Asian, and American haplotypes are small. Numerical characteristics (sequence descriptors) applied in the studies can recognize the differences. The concept of creating descriptors of 4D-dynamic graphs has been borrowed from classical dynamics; these are coordinates of the centers or mass and moments of inertia of 4D-dynamic graphs. Based on these descriptors, classification maps are constructed. The concentrations of points in the maps indicate one Polish haplotype (EmPL9) of Asian origin.

show abstract

“…For the unaligned sequences, it is a way toward alignment-free approach of sequence comparison. A quite number of studies have shown the advantages of using alignment-free algorithms over alignment-base methods due to their computational limitations such as alignment errors and incongruences, whole genome comparison and etc (Susana and Jonas, 2003;Chan and Ragan, 2013;Zielezinski et al, 2017;Zielezinski et al, 2019;Saw, et al, 2019).…”

Section: Alignment Independencymentioning

confidence: 99%

Application of Statistical Mirroring in Biological Sequence Analysis

Abdullahi¹

2019

Preprint

View full text Add to dashboard Cite

Sequence alignment and comparison through pairwise, multiple, global and local techniques are the main principles that underpin comparative genomics. However, most of the algorithms used are alignment-based which imposed some limitations on their use and application. In an attempt to provide an alignment-free alternative approaches, a methodology of comparative optinalysis and statistical mirroring was used and adopted to provide a suitable alternative for multiple genomic sequence comparison. In this article, methods comparison with MUSCLE, MUFFT, Clustal Omega, and T-Coffee was designed to assess the suitability and statistical power of statistical mirroring as an alternative method for multiple genomic sequences comparison using different sets of logically generated biological sequence datasets with different problems and computational complications. The results of the comparisons validate that statistical mirroring is a suitable alignment-free alternative approach for multiple genomic sequence comparison. The applied method (statistical mirroring) distinguishes itself over MUSCLE, MUFFT, Clustal Omega, and T-Coffee in specificity to a position-specific changes, specificity to a base-specific changes, cladogram and phylogenetic linearity, alignment independency, computational simplicity, and limit of input capacity.

show abstract

Alignment-free method for DNA sequence clustering using Fuzzy integral similarity

Cited by 21 publications

References 62 publications

Non-standard bioinformatics characterization of SARS-CoV-2

Non-standard bioinformatics characterization of SARS-CoV-2

4D-Dynamic Representation of DNA/RNA Sequences: Studies on Genetic Diversity of Echinococcus multilocularis in Red Foxes in Poland

Application of Statistical Mirroring in Biological Sequence Analysis

Contact Info

Product

Resources

About