Abstract
Models that rely exclusively on the Markov property, usually known as finite-context models, can model DNA sequences without considering mechanisms that take direct advantage of exact and approximate repeats. These models provide probability estimates that depend on the recent past of the sequence and have been used for data compression. In this paper, we investigate some properties of the finite-context models and we use these properties in order to improve the compression. The results are presented using the human genome as example.
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Pratas, D., Pinho, A.J. (2011). Compressing the Human Genome Using Exclusively Markov Models. In: Rocha, M.P., RodrÃguez, J.M.C., Fdez-Riverola, F., Valencia, A. (eds) 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011). Advances in Intelligent and Soft Computing, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19914-1_29
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DOI: https://doi.org/10.1007/978-3-642-19914-1_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19913-4
Online ISBN: 978-3-642-19914-1
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