Adaptive models for gene networks.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Shin, Y-J; Sayed, AH; Shen, X

Published Date

  • January 2012

Published In

Volume / Issue

  • 7 / 2

Start / End Page

  • e31657 -

PubMed ID

  • 22359614

Pubmed Central ID

  • 22359614

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

International Standard Serial Number (ISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0031657

Language

  • eng