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RECOMB International Workshop on Comparative Genomics

RECOMB-CG 2010: Comparative Genomics pp 149–160Cite as

A Simple Measure of the Dynamics of Segmented Genomes: An Application to Influenza

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6398))

Abstract

The severity of influenza epidemics, which can potentially become a pandemic, has been very difficult to predict. However, past efforts were focusing on gene-by-gene approaches, while it is acknowledged that the whole genome dynamics contribute to the severity of an epidemic. Here, putting this rationale into action, I describe a simple measure of the amount of reassortment that affects influenza at a genomic scale during a particular year. The analysis of 530 complete genomes of the H1N1 subtype, sampled over eleven years, shows that the proposed measure explains 58% of the variance in the prevalence of H1 influenza in the US population. The proposed measure, denoted nRF, could therefore improve influenza surveillance programs at a minimal cost.

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Author information

Authors and Affiliations

  1. Department of Biology and Center for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, ON, K1N 6N5, Canada

    Stéphane Aris-Brosou

  2. Department of Mathematics and Statistics, University of Ottawa, Canada

    Stéphane Aris-Brosou

Authors
  1. Stéphane Aris-Brosou
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Editor information

Editors and Affiliations

  1. INRIA Rhône-Alpes, Université de Lyon 1, Villeurbanne, France

    Eric Tannier

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Aris-Brosou, S. (2010). A Simple Measure of the Dynamics of Segmented Genomes: An Application to Influenza. In: Tannier, E. (eds) Comparative Genomics. RECOMB-CG 2010. Lecture Notes in Computer Science(), vol 6398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16181-0_13

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  • DOI: https://doi.org/10.1007/978-3-642-16181-0_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16180-3

  • Online ISBN: 978-3-642-16181-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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