DNA序列的最大频繁模式挖掘

S. Bai, Sixue Bai
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引用次数: 14

摘要

DNA序列数据是生物学数据中基础而重要的数据之一。DNA序列模式挖掘得到了广泛的关注和迅速的发展。传统的序列模式挖掘算法在处理DNA序列时会产生大量的冗余模式。最大频率模式更适合于表达DNA序列的功能和结构。针对DNA序列的特点,本文提出了一种最大模式段连接算法(jmps),用于DNA序列的最大频繁模式挖掘。首先,基于邻域生成最大频繁模式段。然后,将上述片段组合在一起,可以得到更长的最大频繁模式,同时删除非最大模式。该算法能有效地处理DNA序列数据。
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The Maximal Frequent Pattern mining of DNA sequence
The DNA sequence data is one of the basic and important data among biological data. The DNA sequence pattern mining has got wide attention and rapid development. Traditional algorithms for the sequential pattern mining may generate lots of redundant patterns when dealing with the DNA sequence. The Maximal Frequent Pattern is preferable to express the function and structure of the DNA sequence. Base on the characteristics of the DNA sequence, the author develops the Joined Maximal Pattern Segments algorithm—JMPS, for the maximal frequent patterns mining of the DNA sequence. First, the maximal frequent pattern segments base on adjacent generated. Then, longer Maximal Frequent Pattern can be obtained by combining the above segments, at the same time deleting the Non-maximal patterns. The algorithm can deal with the DNA sequence data efficiently.
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