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For aligning DNA sequences that differ only by sequencing errors, or by equivalent errors from other sources, a greedy algorithm can be much faster than traditional dynamic programming approaches and yet produce an alignment that is guaranteed to be theoretically optimal. We introduce a new greedy alignment algorithm with particularly good performance and show that it computes the same alignment as does a certain dynamic programming algorithm, while executing over 10 times faster on appropriate data. An implementation of this algorithm is currently used in a program that assembles the UniGene database at the National Center for Biotechnology Information.
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Zheng Zhang
Scott Schwartz
Lukas Wagner
Journal of Computational Biology
National Institutes of Health
Pennsylvania State University
National Center for Biotechnology Information
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Zhang et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69d900bea5ecc596b5d190a6 — DOI: https://doi.org/10.1089/10665270050081478
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