Similarity Estimation Between DNA Sequences Based on Local Pattern Histograms of Binary Images

Graphical representation of DNA sequences is one of the most popular techniques for alignment-free sequence comparison. Here, we propose a new method for the feature extraction of DNA sequences represented by binary images, by estimating the similarity between DNA sequences using the frequency histo...

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Bibliographic Details
Main Authors: Yusei Kobori, Satoshi Mizuta
Format: Article
Language:English
Published: Oxford University Press 2016-04-01
Series:Genomics, Proteomics & Bioinformatics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1672022916300353
Description
Summary:Graphical representation of DNA sequences is one of the most popular techniques for alignment-free sequence comparison. Here, we propose a new method for the feature extraction of DNA sequences represented by binary images, by estimating the similarity between DNA sequences using the frequency histograms of local bitmap patterns of images. Our method shows linear time complexity for the length of DNA sequences, which is practical even when long sequences, such as whole genome sequences, are compared. We tested five distance measures for the estimation of sequence similarities, and found that the histogram intersection and Manhattan distance are the most appropriate ones for phylogenetic analyses.
ISSN:1672-0229