|Title||Adaptive models for gene networks.|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||Y-J Shin, AH Sayed, and X Shen|
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.
|Short Title||PloS one|