Hidden Markov Modelling Techniques for Haplotype Analysis

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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.

Mikko Koivisto, Teemu Kivioja, Heikki Mannila, Pas

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ALT 2004 | Hidden Markov Model | Machine Learning | Minimum Description Length | Real Sets |

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Added	15 Mar 2010
Updated	15 Mar 2010
Type	Conference
Year	2004
Where	ALT
Authors	Mikko Koivisto, Teemu Kivioja, Heikki Mannila, Pasi Rastas, Esko Ukkonen

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Hidden Markov Modelling Techniques for Haplotype Analysis

ALT 2004 | Hidden Markov Model | Machine Learning | Minimum Description Length | Real Sets |

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