A Greedy Algorithm for Aligning DNA Sequences

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. Key words: sequence alignment, greedy algorithms, dynamic programming.

• Type: Journal
• Year: 2000
• Where: JCB
• Authors: Zheng Zhang 0004, Scott Schwartz, Lukas Wagner, Webb Miller
• Keywords: Algorithms, Dynamic Programming, Greedy Algorithms, JCB 2000