贪婪算法
动态规划
计算机科学
算法
非重复序列
基因组
生物
遗传学
表达序列标记
基因
作者
Zheng Zhang,Scott Schwartz,Lukas Wagner,Webb Miller
标识
DOI:10.1089/10665270050081478
摘要
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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