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Discovering Motiv Based Association Rules in a Set of DNA Sequences

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2005))

Abstract

The research of similarity between DNA sequences is an important problem in Bio-Informatics. In the traditional approach, the dynamic programming based pair-wise alignment is used for measuring the similarity between two sequences. This method does not work well in a large data set. In this paper, we consider motifs like the phrase of document and use text mining techniques for finding the frequent motifs, maximal frequent motifs, motif based association rules in a group of genes.

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References

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© 2001 Springer-Verlag Berlin Heidelberg

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Kiem, H., Phuc, D. (2001). Discovering Motiv Based Association Rules in a Set of DNA Sequences. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_47

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  • DOI: https://doi.org/10.1007/3-540-45554-X_47

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43074-2

  • Online ISBN: 978-3-540-45554-7

  • eBook Packages: Springer Book Archive

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