ArticleBiophysical journal2010
Architecture-dependent robustness and bistability in a class of genetic circuits.
Article in Biophysical journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Synthetic robust perfect adaptation achieved by negative feedback coupling with linear weak positive feedback.Nucleic acids research · 2022Article
- Robustness of a biomolecular oscillator to pulse perturbations.IET systems biology · 2020Article
- Modeling the Sex Differences and Interindividual Variability in the Activity of the Hypothalamic-Pituitary-Adrenal Axis.Endocrinology · 2017Article
- Causal drift, robust signaling, and complex disease.PloS one · 2015Article
- Architecture-dependent robustness in a class of multiple positive feedback loops.IET systems biology · 2013Article
- Efficient characterization of high-dimensional parameter spaces for systems biology.BMC systems biology · 2011Article
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Authors and funding
4 authors.
Funding
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Abstract
Understanding the relationship between genotype and phenotype is a challenge in systems biology. An interesting yet related issue is why a particular circuit topology is present in a cell when the same function can supposedly be obtained from an alternative architecture. Here we analyzed two topologically equivalent genetic circuits of coupled positive and negative feedback loops, named NAT and ALT circuits, respectively. The computational search for the oscillation volume of the entire biologically reasonable parameter region through large-scale random samplings shows that the NAT circuit exhibits a distinctly larger fraction of the oscillatory region than the ALT circuit. Such a global robustness difference between two circuits is supplemented by analyzing local robustness, including robustness to parameter perturbations and to molecular noise. In addition, detailed dynamical analysis shows that the molecular noise of both circuits can induce transient switching of the different mechanism between a stable steady state and a stable limit cycle. Our investigation on robustness and dynamics through examples provides insights into the relationship between network architecture and its function.
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