Abstract
DNA sequence analysis methods, such as motif discovery, gene detection or phylogeny reconstruction, can often provide important input for biological studies. Many of such methods require a background model, representing the expected distribution of short substrings in a given DNA region. Most current techniques for modeling this distribution disregard the evolutionary processes underlying DNA formation. We propose a novel approach for modeling DNA k-mer distribution that is capable of taking the notions of evolution and natural selection into account. We derive a computionally tractable approximation for estimating k-mer probabilities at genetic equilibrium, given a description of evolutionary processes in terms of fitness and mutation probabilities. We assess the goodness of this approximation via numerical experiments. Besides providing a generative model for DNA sequences, our method has further applications in motif discovery.
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Kull, M., Tretyakov, K., Vilo, J. (2010). An Evolutionary Model of DNA Substring Distribution. In: Elomaa, T., Mannila, H., Orponen, P. (eds) Algorithms and Applications. Lecture Notes in Computer Science, vol 6060. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12476-1_10
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DOI: https://doi.org/10.1007/978-3-642-12476-1_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12475-4
Online ISBN: 978-3-642-12476-1
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