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A Markovian Approach for the Segmentation of Chimpanzee Genome

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Bioinformatics Research and Development (BIRD 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4414))

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Abstract

Hidden Markov models (HMMs) are effective tools to detect series of statistically homogeneous structures, but they are not well suited to analyse complex structures such as DNA sequences. Numerous methodological difficulties are encountered when using HMMs to model non geometric distribution such as exons length, to segregate genes from transposons or retroviruses, or to determine the isochore classes of genes. The aim of this paper is to suggest new tools for the exploration of genome data. We show that HMMs can be used to analyse complex gene structures with bell-shaped length distribution by introducing macros-states. Our HMMs methods take into account many biological properties and were developped to model the isochore organisation of the chimpanzee genome which is considered as a fondamental level of genome organisation. A clear isochore structure in the chimpanzee genome, correlated with the gene density and guanine-cytosine content, has been identified.

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Authors and Affiliations

  1. UMR 5558 CNRS Biométrie et Biologie Evolutive, Université Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1818, 69622 Villeurbanne Cedex - France and PRABI (Rhône Alpes Bioinformatics Center),  

    Christelle Melodelima & Christian Gautier

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  1. Christelle Melodelima
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  2. Christian Gautier
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Sepp Hochreiter Roland Wagner

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Melodelima, C., Gautier, C. (2007). A Markovian Approach for the Segmentation of Chimpanzee Genome. In: Hochreiter, S., Wagner, R. (eds) Bioinformatics Research and Development. BIRD 2007. Lecture Notes in Computer Science(), vol 4414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71233-6_20

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  • DOI: https://doi.org/10.1007/978-3-540-71233-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71232-9

  • Online ISBN: 978-3-540-71233-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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