首页> 外文会议>International workshop on algorithms in bioinformatics >Extracting Common Motifs under the Levenshtein Measure: Theory and Experimentation
【24h】

Extracting Common Motifs under the Levenshtein Measure: Theory and Experimentation

机译:提取Levenshtein测量下的共同主题:理论与实验

获取原文

摘要

Using our techniques for extracting approximate non-tandem repeats[1] on well constructed maximal models, we derive an algorithm to find common motifs of length P that occur in N sequences with at most D differences under the Edit distance metric. We compare the effectiveness of our algorithm with the more involved algorithm of Sagot[17] for Edit distance on some real sequences. Her method has not been implemented before for Edit distance but only for Hamming distance[12,20]. Our resulting method turns out to be simpler and more efficient theoretically and also in practice for moderately large P and D.
机译:使用我们在良好构造的最大模型上提取近似非串联重复[1]的技术,我们推导了一种算法,找到在N个序列中发生的长度P的常见图案,其在编辑距离度量下的大多数差异。我们将算法与更多涉及的Sagot算法[17]进行比较,以便在某些真实序列上编辑距离。她的方法尚未在编辑距离之前实施,但仅用于汉明距离[12,20]。理论上,我们的由此产生的方法变得更简单,更高效地,并且在实践中适用于中等大的P和D.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号