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PatternHunter: faster and more sensitive homology search

机译:PatternHunter:更快,更敏感的同源性搜索

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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.
机译:动机:基因组学和蛋白质组学研究通常依赖于同源性搜索,其基础是寻找短种子匹配的策略,然后对其进行扩展。爆炸性的基因组数据增长为DNA同源性搜索技术带来了难题:增大种子大小会降低灵敏度,而减小种子大小会降低计算速度。结果:我们提出了一种新的同源性搜索算法“ PatternHunter”,该算法使用新颖的种子模型来提高灵敏度,并使用新的命中处理技术来显着提高速度。在Blast灵敏度级别,PatternHunter能够在桌面上仅几个小时内找到与人类染色体一样大的序列之间的同源性。

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