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
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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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