Application of Graph Entropy in CRISPR and Repeats Detection in DNA Sequences

Autor:	Jharna D. Sengupta, Dipendra C. Sengupta
Rok vydání:	2016
Předmět:	Genetics Tandem repeat CRISPR Entropy (information theory) Direct repeat General Medicine Bacterial genome size Computational biology Biology Quantitative Biology::Genomics Square matrix Genome DNA sequencing
Zdroj:	Computational Molecular Bioscience. :41-51
ISSN:	2165-3453 2165-3445
DOI:	10.4236/cmb.2016.63004
Popis:	We analyzed DNA sequences using a new measure of entropy. The general aim was to analyze DNA sequences and find interesting sections of a genome using a new formulation of Shannon like entropy. We developed this new measure of entropy for any non-trivial graph or, more broadly, for any square matrix whose non-zero elements represent probabilistic weights assigned to connections or transitions between pairs of vertices. The new measure is called the graph entropy and it quantifies the aggregate indeterminacy effected by the variety of unique walks that exist between each pair of vertices. The new tool is shown to be uniquely capable of revealing CRISPR regions in bacterial genomes and to identify Tandem repeats and Direct repeats of genome. We have done experiment on 26 species and found many tandem repeats and direct repeats (CRISPR for bacteria or archaea). There are several existing separate CRISPR or Tandem finder tools but our entropy can find both of these features if present in genome.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e2afb55b0194cfb0acd9ba4eec730889 https://doi.org/10.4236/cmb.2016.63004 Zobrazit plný text záznamu