ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2009
Spectral solutions to stochastic models of gene expression with bursts and regulation.
Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Gene expression model inference from snapshot RNA data using Bayesian non-parametrics.Nature computational science · 2023Article
- Queuing Models of Gene Expression: Analytical Distributions and Beyond.Biophysical journal · 2020Article
- A Mechanochemical Model of Transcriptional Bursting.Biophysical journal · 2020Article
- Critical slowing down in biochemical networks with feedback.Physical review. E · 2019Article
- Universality of biochemical feedback and its application to immune cells.Physical review. E · 2019Article
- Noise Expands the Response Range of the Bacillus subtilis Competence Circuit.PLoS computational biology · 2016Article
- Extending the dynamic range of transcription factor action by translational regulation.Physical review. E · 2016Article
- Probability distributions for multimeric systems.Journal of mathematical biology · 2016Article
- A Hybrid of the Chemical Master Equation and the Gillespie Algorithm for Efficient Stochastic Simulations of Sub-Networks.PloS one · 2016Article
- Potential unsatisfiability of cyclic constraints on stochastic biological networks biases selection towards hierarchical architectures.Journal of the Royal Society, Interface · 2015Article
- The utility of simple mathematical models in understanding gene regulatory dynamics.In silico biology · 2015Review
- A computational framework for analyzing stochasticity in gene expression.PLoS computational biology · 2014Article
- Promoter-mediated transcriptional dynamics.Biophysical journal · 2014Article
- Spatial partitioning improves the reliability of biochemical signaling.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- An effective method for computing the noise in biochemical networks.The Journal of chemical physics · 2013Article
- Analytical distribution and tunability of noise in a model of promoter progress.Biophysical journal · 2012Article
- Cooperative binding of transcription factors promotes bimodal gene expression response.PloS one · 2012Article
- Statistical method for revealing form-function relations in biological networks.Proceedings of the National Academy of Sciences of the United States of America · 2011Article
- Information-optimal transcriptional response to oscillatory driving.Physical review letters · 2010Article
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3 authors.
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Abstract
Signal-processing molecules inside cells are often present at low copy number, which necessitates probabilistic models to account for intrinsic noise. Probability distributions have traditionally been found using simulation-based approaches which then require estimating the distributions from many samples. Here we present in detail an alternative method for directly calculating a probability distribution by expanding in the natural eigenfunctions of the governing equation, which is linear. We apply the resulting spectral method to three general models of stochastic gene expression: a single gene with multiple expression states (often used as a model of bursting in the limit of two states), a gene regulatory cascade, and a combined model of bursting and regulation. In all cases we find either analytic results or numerical prescriptions that greatly outperform simulations in efficiency and accuracy. In the last case, we show that bimodal response in the limit of slow switching is not only possible but optimal in terms of information transmission.
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