PatternHunter: faster and more sensitive homology search

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ID: 302278
2002
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Abstract
Abstract Motivation: Genomics and proteomics studies routinely depend on homology searches based on the strategy of finding short seed matches which are then extended. The exploding genomic data growth presents a dilemma for DNA homology search techniques: increasing seed size decreases sensitivity whereas decreasing seed size slows down computation. Results: We present a new homology search algorithm ‘PatternHunter’ that uses a novel seed model for increased sensitivity and new hit-processing techniques for significantly increased speed. At Blast levels of sensitivity, PatternHunter is able to find homologies between sequences as large as human chromosomes, in mere hours on a desktop. Availability: PatternHunter is available at http://www.bioinformaticssolutions.com, as a commercial package. It runs on all platforms that support Java. PatternHunter technology is being patented; commercial use requires a license from BSI, while non-commercial use will be free. Contact: mli@cs.ucsb.edu
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openalex_W2128591967 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bin Ma, John Tromp, Ming Li
Journal BMC Bioinformatics
Year 2002
DOI
10.1093/bioinformatics/18.3.440
URL
https://academic.oup.com/bioinformatics/article-pdf/18/3/440/48850317/bioinformatics_18_3_440.pdf
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