Abstract:
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. Traditio...Show MoreMetadata
Abstract:
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 nonmaximal patterns. The algorithm can deal with the DNA sequence data efficiently.
Published in: 2009 IEEE International Conference on Granular Computing
Date of Conference: 17-19 August 2009
Date Added to IEEE Xplore: 22 September 2009
Print ISBN:978-1-4244-4830-2