• DocumentCode
    130141
  • Title

    Modeling the genetic information transmission based on Colored Petri Nets

  • Author

    Jinliang Yang ; Jian Lian ; Haitao Pu ; Rui Gao

  • Author_Institution
    Dept. of Electr. Eng. & Inf. Technol., Shandong Univ. of Sci. & Technol., Jinan, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    1025
  • Lastpage
    1029
  • Abstract
    In molecular biology, gene expression is the basic process in living systems and it describes the process of genetic information transfer from DNA to protein. Understanding and description of this process is mainly based on the traditional textual representation model. As a mature mathematical theory tools used in the process analysis, Colored Petri Net (CPN) provides a new and effective theoretical methods for studying the basic processes in living systems. In this paper, we propose a CPN model to describe the process of genetic information transfer, which successfully characterized the genetic information from DNA transcribes to mRNA and then translates to protein. The operation of this model can be divided into five stages: initialization, transcription, determination of the start codon, determination of the stop codons, and translation. This model is conducive to understand and analysis the microbiological processes intuitively.
  • Keywords
    Petri nets; genetics; molecular biophysics; proteins; CPN; DNA; colored Petri nets; gene expression; genetic information transfer; genetic information transmission modeling; mRNA; microbiological process; molecular biology; protein; stop codons; textual representation model; Amino acids; Biological system modeling; Color; DNA; Hidden Markov models; Mathematical model; Amino acid codon; Colored Petri Net; Gene information transfer; Molecular biology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2014 IEEE International Conference on
  • Conference_Location
    Hailar
  • Type

    conf

  • DOI
    10.1109/ICInfA.2014.6932800
  • Filename
    6932800