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 Set produce an alignment that is guaranteed to be theoretically optimal. We introduce a nem 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.

对于仅因测序错误或其他来源的等效错误而不同的DNA序列进行比对，贪心算法可能比传统的动态规划方法快得多，并且能够产生在理论上保证是最优的比对结果。我们引入了一种性能特别好的新贪心比对算法，并表明它计算出的比对结果与某种动态规划算法相同，而在合适的数据上执行速度快10倍以上。该算法的一种实现目前被用于美国国家生物技术信息中心组装UniGene数据库的一个程序中。