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Co-evolution and Information Signals in Biological Sequences

  • Conference paper
Theory and Applications of Models of Computation (TAMC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5532))

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Abstract

Information content of a pool of sequences has been defined in information theory through enthropic measures aimed to capture the amount of variability within sequences. When dealing with biological sequences coding for proteins, a first approach is to align these sequences to estimate the probability of each amino-acid to occur within alignment positions and to combine these values through an “entropy” function whose minimum corresponds to the case where for each position, each amino-acid has the same probability to occur. This model is too restrictive when the purpose is to evaluate sequence constraints that have to be conserved to maintain the function of the proteins under random mutations. In fact, co-evolution of amino-acids appearing in pairs or tuplets of positions in sequences constitutes a fine signal of important structural, functional and mechanical information for protein families. It is clear that classical information theory should be revisited when applied to biological data. A large number of approaches to co-evolution of biological sequences have been developed in the last seven years. We present a few of them, discuss their limitations and some related questions, like the generation of random structures to validate predictions based on co-evolution, which appear crucial for new advances in structural bioinformatics.

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Author information

Authors and Affiliations

  1. Département d’Informatique, Université Pierre et Marie Curie-Paris 6,  

    Alessandra Carbone

  2. Génomique Analytique, FRE3214 CNRS-UPMC, 15, Rue de l’Ecole de Médecine, 75005, Paris,  

    Linda Dib

Authors
  1. Alessandra Carbone
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  2. Linda Dib
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Texas A&M University, College Station, 77843, Texas, USA

    Jianer Chen

  2. School of Mathematics, University of Leeds, LS2 9JT, U.K.

    S. Barry Cooper

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Carbone, A., Dib, L. (2009). Co-evolution and Information Signals in Biological Sequences. In: Chen, J., Cooper, S.B. (eds) Theory and Applications of Models of Computation. TAMC 2009. Lecture Notes in Computer Science, vol 5532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02017-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-02017-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

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  • Online ISBN: 978-3-642-02017-9

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