TITLE:
Application of Graph Entropy in CRISPR and Repeats Detection in DNA Sequences
AUTHORS:
Dipendra C. Sengupta, Jharna D. Sengupta
KEYWORDS:
CRISPR, Graph Entropy, Tandem Repeats, DNA Sequences
JOURNAL NAME:
Computational Molecular Bioscience,
Vol.6 No.3,
October
26,
2016
ABSTRACT: 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.