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Association Matrix Method and Its Applications in Mining DNA Sequences

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 965))

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Abstract

Many mining algorithms have been presented for business big data such as marketing baskets, but they cannot be effective or efficient for mining DNA sequences, any of which is typically with a small alphabet but a much long sizes. This paper will design a compact data structure called Association Matrix, and give an algorithm to specially mine long DNA sequences. The Association Matrix is novel in-memory data structure, which can be so compact that it can deal with super long DNA sequences in a limited memory spaces. Such, based on the Association Matrix structure, we can design the algorithms for efficiently mining key segments from DNA sequences. Additionally, we will show our related experiments and results in this paper.

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Acknowledgements

I am deeply indebted to the NSFC (China National Science Foundation of China), for its funding support with Number 61773415 makes the related re-search of this paper better.

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Correspondence to Guojun Mao .

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Mao, G. (2020). Association Matrix Method and Its Applications in Mining DNA Sequences. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 965. Springer, Cham. https://doi.org/10.1007/978-3-030-20454-9_15

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  • DOI: https://doi.org/10.1007/978-3-030-20454-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20453-2

  • Online ISBN: 978-3-030-20454-9

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