title: Clustering of giant virus-DNA based on variations in local entropy.
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.
authors.affiliation: Department of Electrical Engineering, IIT Delhi, Hauz Khas, New Delhi 110016, India. rbose.iitd@gmail.com.
authors.forename: Ranjan
authors.initials: R
authors.lastname: Bose
authors.affiliation: Department of Biology, Technische Universität Darmstadt, 64287 Darmstadt, Germany. Thiel@bio.tu-darmstadt.de.
authors.forename: Gerhard
authors.initials: G
authors.lastname: Thiel
authors.affiliation: Department of Biology, Technische Universität Darmstadt, 64287 Darmstadt, Germany. Hamacher@bio.tu-darmstadt.de.
authors.forename: Kay
authors.initials: K
authors.lastname: Hamacher
mesh_terms: D002708:Chlorella / Q000821:virology; D016000:Cluster Analysis; D019295:Computational Biology; D004279:DNA, Viral; D019143:Evolution, Molecular; D016679:Genome, Viral; D023281:Genomics; D054884:Host-Pathogen Interactions; D010802:Phylogeny; D010942:Plant Viruses / Q000145:classification* / Q000235:genetics*
chemical_list: D004279:DNA, Viral