Optimal path to epigenetic switching
Copyright policy )Optimal path to epigenetic switching
We use large deviation methods to calculate rates of noise-induced transitions between states in multistable genetic networks. We analyze a synthetic biochemical circuit, the toggle switch, and compare the results to those obtained from a numerical solution of the master equation.
5 pages. 2 figures, uses revtex 4. PR-E reviewed for publication
- Clarke University United States
- Clark University United States
- Boston University United States
- Rutgers, The State University of New Jersey United States
Transcriptional Activation, Molecular Networks (q-bio.MN), fluids & plasmas, physiological, Phage-lambda, Signal transduction, 530, 510, Transcriptional activation, Models, Genes, Regulator, Cell Behavior (q-bio.CB), Escherichia coli, Transcription factors, mathematical, Animals, Humans, Quantitative Biology - Molecular Networks, Computer Simulation, Gene-expression, Adaptation, Robustness, Clocks, Stochasticity, Models, Genetic, Physics, Computer simulation, Adaptation, Physiological, Physical sciences, Genes, regulator, FOS: Biological sciences, Quantitative Biology - Cell Behavior, genetic, Science & technology, Noise, Kramers, Algorithms, Signal Transduction, Transcription Factors
Transcriptional Activation, Molecular Networks (q-bio.MN), fluids & plasmas, physiological, Phage-lambda, Signal transduction, 530, 510, Transcriptional activation, Models, Genes, Regulator, Cell Behavior (q-bio.CB), Escherichia coli, Transcription factors, mathematical, Animals, Humans, Quantitative Biology - Molecular Networks, Computer Simulation, Gene-expression, Adaptation, Robustness, Clocks, Stochasticity, Models, Genetic, Physics, Computer simulation, Adaptation, Physiological, Physical sciences, Genes, regulator, FOS: Biological sciences, Quantitative Biology - Cell Behavior, genetic, Science & technology, Noise, Kramers, Algorithms, Signal Transduction, Transcription Factors
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