A Greedy Algorithm for Aligning DNA Sequences
Zheng Zhang(Pennsylvania State University), Scott Schwartz(Pennsylvania State University), Lukas Wagner(National Institutes of Health), Webb Miller(Pennsylvania State University)
Cited by 5,629
Abstract
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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