Adaptive Models for Gene Networks

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.


Published in:
PLoS One, 7, 2, e31657
Year:
2012
Publisher:
Public Library of Science
ISSN:
1932-6203
Laboratories:




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