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Core Information
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| Title: |
Chaotic gene regulatory networks can be robust against mutations and noise |
| Abstract: |
Robustness to mutations and noise has been shown to evolve through stabilizing selection for optimal phenotypes in model gene regulatory networks. The ability to evolve robust mutants is known to depend on the network architecture. How do the dynamical properties and state-space structures of networks with high and low robustness differ? Does selection operate on the global dynamical behavior of the networks? What kind of state-space structures are favored by selection? We provide damage propagation analysis and an extensive statistical analysis of state spaces of these model networks to show that the change in their dynamical properties due to stabilizing selection for optimal phenotypes is minor. Most notably, the networks that are most robust to both mutations and noise are highly chaotic. Certain properties of chaotic networks, such as being able to produce large attractor basins, can be useful for maintaining a stable gene-expression pattern. Our findings indicate that conventional measures of stability, such as damage propagation, do not provide much information about robustness to mutations or noise in model gene regulatory networks.
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| Keywords: |
Gene regulatory network, Random threshold network, Robustness, State space structure |
Author Information
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| 1. | Sevim, Volkan | [ FSU/SCS/MARTECH/Physics ] | Graduate | | 2. | Rikvold, Per Arne | [ FSU/SCS/MARTECH/Physics/NHMFL ] | Neither |
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Detailed Scientific Article Information
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| Journal Name: |
Journal of Theoretical Biology |
| Volume: |
253 |
| Page Range: |
323-332 |
Article Number: |
Not Provided |
| Number of Pages: |
Not Provided |
| Year of Publication: |
2008 |
| Refereed: |
Yes |
| Digital Object Identifier (DOI), if available: |
10.1016/j.jtbi.2008.03.003 |
| Official Url: |
Not Provided |
| ISSN: |
Not Provided |
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Subjects Information
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1. Biology
2. Physics
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