• DocumentCode
    3538449
  • Title

    Global identifiability of a simple linear model for gene expression analysis

  • Author

    Helmke, U. ; Huper, Knut ; Khammash, Mustafa

  • Author_Institution
    Inst. for Math., Univ. of Wurzburg, Wurzburg, Germany
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    7149
  • Lastpage
    7154
  • Abstract
    Global parameter identifiability of time-invariant linear systems for continuous and sampled output measurements is characterized. New necessary and sufficient conditions for parameter identifiability for linear systems with constant inputs are derived. An application to global identifiability of low dimensional models for gene expression analysis is given.
  • Keywords
    Monte Carlo methods; genetics; linear systems; parameter estimation; time-varying systems; continuous output measurements; gene expression analysis; global parameter identifiability; sampled output measurements; simple linear model; time-invariant linear systems; Biological system modeling; Gene expression; Observability; Polynomials; Proteins; Stochastic processes; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6761023
  • Filename
    6761023
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3538449