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首页> 外文期刊>International journal of data mining and bioinformatics >Analysis of the relationships among Longest Common Subsequences, Shortest Common Supersequences and patterns and its application on pattern discovery in biological sequences
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Analysis of the relationships among Longest Common Subsequences, Shortest Common Supersequences and patterns and its application on pattern discovery in biological sequences

机译:最长共同子序列,最短共同超序列与模式之间的关系分析及其在生物序列模式发现中的应用

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摘要

For a set of multiple sequences, their patterns, Longest Common Subsequences (LCS) and Shortest Common Supersequences (SCS) represent different aspects of these sequences- profile. Revealing the relationship between the patterns and LCS/SCS might provide us with a deeper view of the patterns. In this paper, we have showed that patterns LCS and SCS were closely related to each other. Based on their relations, the PALS algorithms are proposed to discover patterns in a set of biological sequences based on LCS and SCS results. Experiments show that the PALS algorithms are superior in efficiency and accuracy on a variety of sequences.
机译:对于一组多个序列,它们的模式,最长公共子序列(LCS)和最短公共超序列(SCS)代表这些序列配置文件的不同方面。揭示模式与LCS / SCS之间的关系可能为我们提供了对模式的更深入的了解。在本文中,我们表明,模式LCS和SCS彼此密切相关。基于它们之间的关系,提出了PALS算法,以基于LCS和SCS结果发现一组生物序列中的模式。实验表明,PALS算法在各种序列上均具有出色的效率和准确性。

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