Bistability and oscillations in the Huang-Ferrell model of MAPK signaling.
Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2007-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.0030184 |
| _version_ | 1818401202666209280 |
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| author | Liang Qiao Robert B Nachbar Ioannis G Kevrekidis Stanislav Y Shvartsman |
| author_facet | Liang Qiao Robert B Nachbar Ioannis G Kevrekidis Stanislav Y Shvartsman |
| author_sort | Liang Qiao |
| collection | DOAJ |
| description | Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this level of uncertainty, model analysis should emphasize statistics of systems-level properties, rather than the detailed structure of solutions or boundaries separating different dynamic regimes. Based on the combination of random parameter search and continuation algorithms, we developed a methodology for the statistical analysis of mechanistic signaling models. In applying it to the well-studied MAPK cascade model, we discovered a large region of oscillations and explained their emergence from single-stage bistability. The surprising abundance of strongly nonlinear (oscillatory and bistable) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures. We argue that this type of analysis should accompany nonlinear multiparameter studies of stationary as well as transient features in network dynamics. |
| first_indexed | 2024-12-14T07:48:43Z |
| format | Article |
| id | doaj.art-bfb39b0aeb3444ffa4ca80d07d39c2c3 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-14T07:48:43Z |
| publishDate | 2007-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-bfb39b0aeb3444ffa4ca80d07d39c2c32022-12-21T23:10:47ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582007-09-01391819182610.1371/journal.pcbi.0030184Bistability and oscillations in the Huang-Ferrell model of MAPK signaling.Liang QiaoRobert B NachbarIoannis G KevrekidisStanislav Y ShvartsmanPhysicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this level of uncertainty, model analysis should emphasize statistics of systems-level properties, rather than the detailed structure of solutions or boundaries separating different dynamic regimes. Based on the combination of random parameter search and continuation algorithms, we developed a methodology for the statistical analysis of mechanistic signaling models. In applying it to the well-studied MAPK cascade model, we discovered a large region of oscillations and explained their emergence from single-stage bistability. The surprising abundance of strongly nonlinear (oscillatory and bistable) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures. We argue that this type of analysis should accompany nonlinear multiparameter studies of stationary as well as transient features in network dynamics.https://doi.org/10.1371/journal.pcbi.0030184 |
| spellingShingle | Liang Qiao Robert B Nachbar Ioannis G Kevrekidis Stanislav Y Shvartsman Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. PLoS Computational Biology |
| title | Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. |
| title_full | Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. |
| title_fullStr | Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. |
| title_full_unstemmed | Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. |
| title_short | Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. |
| title_sort | bistability and oscillations in the huang ferrell model of mapk signaling |
| url | https://doi.org/10.1371/journal.pcbi.0030184 |
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