Clustering of Giant Virus-DNA Based on Variations in Local EntropyReport as inadecuate




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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.



Abstract 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





Author: Ranjan Bose 1, Gerhard Thiel 2 and Kay Hamacher 2,3,*

Source: http://mdpi.com/



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