• DocumentCode
    1892944
  • Title

    Ab initio exon definition using an information theory-based approach

  • Author

    Rogan, Peter K.

  • Author_Institution
    Univ. of Western Ontario, London, ON
  • fYear
    2009
  • fDate
    18-20 March 2009
  • Firstpage
    847
  • Lastpage
    852
  • Abstract
    Transcribed exons in genes are joined together at donor and acceptor splice sites precisely and efficiently to generate mRNAs capable of being translated into proteins. The sequence variability in individual splice sites can be modeled using Shannon information theory. In the laboratory, the degree of individual splice site use is inferred from the structures of mRNAs and their relative abundance. These structures can be predicted using a bipartite information theory framework that is guided by current knowledge of biological mechanisms for exon recognition. We present the results of this analysis for the complete dataset of all expressed human exons.
  • Keywords
    Monte Carlo methods; bioinformatics; information theory; macromolecules; organic compounds; Ab initio exon definition; Shannon information theory; biological mechanisms; information theory-based approach; mRNA; Bioinformatics; Entropy; Genetic communication; Humans; Information theory; Proteins; RNA; Sensitivity and specificity; Thermodynamics; Upper bound; Biological System Modeling; Genetics; Information Theory; Monte Carlo Methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences and Systems, 2009. CISS 2009. 43rd Annual Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    978-1-4244-2733-8
  • Electronic_ISBN
    978-1-4244-2734-5
  • Type

    conf

  • DOI
    10.1109/CISS.2009.5054835
  • Filename
    5054835