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Adaptive Models for Gene Networks

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  • Yong-Jun Shin
  • Ali H Sayed
  • Xiling Shen

Abstract

Biological systems are often treated as time-invariant by computational models that use fixed parameter values. In this study, we demonstrate that the behavior of the p53-MDM2 gene network in individual cells can be tracked using adaptive filtering algorithms and the resulting time-variant models can approximate experimental measurements more accurately than time-invariant models. Adaptive models with time-variant parameters can help reduce modeling complexity and can more realistically represent biological systems.

Suggested Citation

  • Yong-Jun Shin & Ali H Sayed & Xiling Shen, 2012. "Adaptive Models for Gene Networks," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-6, February.
    • Handle: RePEc:plo:pone00:0031657
    DOI: 10.1371/journal.pone.0031657
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    References listed on IDEAS

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