Abstract
We review recent results on local alignment. We begin with a review of classical methods and early heuristic methods, and then focus on more recent work on the seeding of local alignment. We show that these techniques give a vast improvement in both sensitivity and specificity over previous methods, and can achieve sensitivity at the level of classical algorithms while requiring orders of magnitude less runtime.
Publication types
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Comparative Study
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Evaluation Study
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Research Support, Non-U.S. Gov't
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Review
MeSH terms
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Algorithms*
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Computer Simulation
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Databases, Genetic
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Models, Genetic*
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Models, Statistical
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Pattern Recognition, Automated / methods*
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Pattern Recognition, Automated / trends
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Reproducibility of Results
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Sensitivity and Specificity
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Sequence Alignment / methods*
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Sequence Alignment / trends
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Sequence Analysis / methods*
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Sequence Analysis / trends
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Sequence Homology