Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation

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dc.contributor.author Pal, Mayukha
dc.contributor.author Kiran, V. Satya
dc.contributor.author Rao, P. Madhusudana
dc.contributor.author Manimaran, P.
dc.date.accessioned 2022-03-27T11:46:39Z
dc.date.available 2022-03-27T11:46:39Z
dc.date.issued 2016-08-15
dc.description.abstract We characterized the multifractal nature and power law cross-correlation between any pair of genome sequence through an integrative approach combining 2D multifractal detrended cross-correlation analysis and chaos game representation. In this paper, we have analyzed genomes of some prokaryotes and calculated fractal spectra h(q) and f(α). From our analysis, we observed existence of multifractal nature and power law cross-correlation behavior between any pair of genome sequences. Cluster analysis was performed on the calculated scaling exponents to identify the class affiliation and the same is represented as a dendrogram. We suggest this approach may find applications in next generation sequence analysis, big data analytics etc.
dc.identifier.citation Physica A: Statistical Mechanics and its Applications. v.456
dc.identifier.issn 03784371
dc.identifier.uri 10.1016/j.physa.2016.03.074
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/S0378437116300723
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/14701
dc.subject Chaos game representation
dc.subject Cluster analysis
dc.subject Genome sequences
dc.subject Multifractal detrended cross-correlation analysis
dc.subject Scaling exponent
dc.title Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation
dc.type Journal. Article
dspace.entity.type
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