Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors.
A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.
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Related Subject Headings
- Models, Genetic
- Gene Regulatory Networks
- Fluids & Plasmas
- Algorithms
- 5199 Other physical sciences
- 4901 Applied mathematics
- 0299 Other Physical Sciences
- 0103 Numerical and Computational Mathematics
- 0102 Applied Mathematics
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Models, Genetic
- Gene Regulatory Networks
- Fluids & Plasmas
- Algorithms
- 5199 Other physical sciences
- 4901 Applied mathematics
- 0299 Other Physical Sciences
- 0103 Numerical and Computational Mathematics
- 0102 Applied Mathematics