Abstract
A hidden Markov model is introduced for descriptive modelling the mosaic–like structures of haplotypes, due to iterated recombinations within a population. Methods using the minimum description length principle are given for fitting such models to training data. Possible applications of the models are delineated, and some preliminary analysis results on real sets of haplotypes are reported, demonstrating the potential of our methods.
A research supported by the Academy of Finland under grant 201560
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Koivisto, M., Kivioja, T., Mannila, H., Rastas, P., Ukkonen, E. (2004). Hidden Markov Modelling Techniques for Haplotype Analysis. In: Ben-David, S., Case, J., Maruoka, A. (eds) Algorithmic Learning Theory. ALT 2004. Lecture Notes in Computer Science(), vol 3244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30215-5_4
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DOI: https://doi.org/10.1007/978-3-540-30215-5_4
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