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Inferring latent gene regulatory network kinetics

Author

Listed:
  • González Javier
  • Vujačić Ivan
  • Wit Ernst

    (Mathematics, Statistics and Probability Unit, University of Groningen, Nijenborgh 9, Groningen, Groningen 9747 AG, The Netherlands)

Abstract

Regulatory networks consist of genes encoding transcription factors (TFs) and the genes they activate or repress. Various types of systems of ordinary differential equations (ODE) have been proposed to model these networks, ranging from linear to Michaelis-Menten approaches. In practice, a serious drawback to estimate these models is that the TFs are generally unobserved. The reason is the actual lack of high-throughput techniques to measure abundance of proteins in the cell. The challenge is to infer their activity profile together with the kinetic parameters of the ODE using level expression measurements of the genes they regulate.

Suggested Citation

  • González Javier & Vujačić Ivan & Wit Ernst, 2013. "Inferring latent gene regulatory network kinetics," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(1), pages 109-127, March.
    • Handle: RePEc:bpj:sagmbi:v:12:y:2013:i:1:p:109-127:n:2
    DOI: 10.1515/sagmb-2012-0006
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    References listed on IDEAS

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    1. R. Khanin & V. Vinciotti & V. Mersinias & C. P. Smith & E. Wit, 2007. "Statistical Reconstruction of Transcription Factor Activity Using Michaelis–Menten Kinetics," Biometrics, The International Biometric Society, vol. 63(3), pages 816-823, September.
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