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Open AccessArticle

Clustering of Giant Virus-DNA Based on Variations in Local Entropy

1
Department of Electrical Engineering, IIT Delhi, Hauz Khas, New Delhi 110016, India
2
Department of Biology, Technische Universität Darmstadt, 64287 Darmstadt, Germany
3
Department of Computer Science & Department of Physics, Technische Universität Darmstadt, 64287 Darmstadt, Germany
*
Author to whom correspondence should be addressed.
Viruses 2014, 6(6), 2259-2267; https://doi.org/10.3390/v6062259
Received: 5 February 2014 / Revised: 19 May 2014 / Accepted: 21 May 2014 / Published: 30 May 2014
We present a method for clustering genomic sequences based on variations in local entropy. We have analyzed the distributions of the block entropies of viruses and plant genomes. A distinct pattern for viruses and plant genomes is observed. These distributions, which describe the local entropic variability of the genomes, are used for clustering the genomes based on the Jensen-Shannon (JS) distances. The analysis of the JS distances between all genomes that infect the chlorella algae shows the host specificity of the viruses. We illustrate the efficacy of this entropy-based clustering technique by the segregation of plant and virus genomes into separate bins. View Full-Text
Keywords: information theory; genomic sequences; evolution; phylogeny; virus information theory; genomic sequences; evolution; phylogeny; virus
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MDPI and ACS Style

Bose, R.; Thiel, G.; Hamacher, K. Clustering of Giant Virus-DNA Based on Variations in Local Entropy. Viruses 2014, 6, 2259-2267.

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