Abstract
Long DNA sequences are often heterogeneous in composition. Hidden Markov models are then good statistical tools to identify homogeneous regions of the sequences. We compare different identification algorithms for hidden Markov chains and present some applications to bacterial genomes to illustrate the method.
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© 1998 Springer-Verlag Berlin Heidelberg
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Muri, F. (1998). Modelling Bacterial Genomes Using Hidden Markov Models. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_8
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DOI: https://doi.org/10.1007/978-3-662-01131-7_8
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
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