Search Results for author: Ramon Grima

Found 14 papers, 3 papers with code

Analysis of a detailed multi-stage model of stochastic gene expression using queueing theory and model reduction

no code implementations23 Jan 2024 Muhan Ma, Juraj Szavits-Nossan, Abhyudai Singh, Ramon Grima

Our results delineate the region of parameter space where conventional models give qualitatively incorrect results and provide insight into how the number of processing stages, e. g. the number of rate-limiting steps in initiation, splicing and mRNA degradation, shape stochastic gene expression by modulation of molecular memory.

Solving stochastic gene expression models using queueing theory: a tutorial review

no code implementations6 Jul 2023 Juraj Szavits-Nossan, Ramon Grima

Stochastic models of gene expression are typically formulated using the chemical master equation, which can be solved exactly or approximately using a repertoire of analytical methods.

Uncovering the effect of RNA polymerase steric interactions on gene expression noise: analytical distributions of nascent and mature RNA numbers

no code implementations11 Apr 2023 Juraj Szavits-Nossan, Ramon Grima

Here we construct a model of gene expression describing promoter switching between inactive and active states, binding of RNA polymerases in the active state, their stochastic movement including steric interactions along the gene, and their unbinding leading to a mature transcript that subsequently decays.

Bayesian learning of effective chemical master equations in crowded intracellular conditions

1 code implementation11 May 2022 Svitlana Braichenko, Ramon Grima, Guido Sanguinetti

Biochemical reactions inside living cells often occur in the presence of crowders -- molecules that do not participate in the reactions but influence the reaction rates through excluded volume effects.

Bayesian Optimisation

Regulation of stem cell dynamics through volume exclusion

no code implementations19 Apr 2022 Rodrigo García-Tejera, Linus Schumacher, Ramon Grima

Here, we propose the birth-death process with volume exclusion (vBD), a variation of the birth-death process that considers crowding effects, such as may arise due to limited space in a stem cell niche.

MomentClosure.jl: automated moment closure approximations in Julia

1 code implementation12 May 2021 Augustinas Sukys, Ramon Grima

MomentClosure. jl is a Julia package providing automated derivation of the time-evolution equations of the moments of molecule numbers for virtually any chemical reaction network using a wide range of moment closure approximations.

Steady-state fluctuations of a genetic feedback loop with fluctuating rate parameters using the unified colored noise approximation

no code implementations4 Apr 2020 James Holehouse, Abhishek Gupta, Ramon Grima

A common model of stochastic auto-regulatory gene expression describes promoter switching via cooperative protein binding, effective protein production in the active state and dilution of proteins.

Translation

Small protein number effects in stochastic models of autoregulated bursty gene expression

no code implementations8 Jan 2020 Chen Jia, Ramon Grima

Furthermore we show that our model predictions for the protein number distribution are significantly different from those of Kumar et al. when the protein mean is small, gene switching is fast, and protein binding is faster than unbinding.

Exact solution of stochastic gene expression models with bursting, cell cycle and replication dynamics

1 code implementation9 Dec 2019 Casper H. L. Beentjes, Ruben Perez-Carrasco, Ramon Grima

We show that protein distributions are well approximated by the solution of implicit models (a negative binomial) when the mean number of mRNAs produced per cycle is low and the cell cycle length variability is large.

Efficient Low-Order Approximation of First-Passage Time Distributions

no code implementations1 Jun 2017 David Schnoerr, Botond Cseke, Ramon Grima, Guido Sanguinetti

We consider the problem of computing first-passage time distributions for reaction processes modelled by master equations.

Bayesian Inference Sequential Bayesian Inference

Approximation and inference methods for stochastic biochemical kinetics - a tutorial review

no code implementations23 Aug 2016 David Schnoerr, Guido Sanguinetti, Ramon Grima

In summary, this review gives a self-contained introduction to modelling, approximations and inference methods for stochastic chemical kinetics.

Cox process representation and inference for stochastic reaction-diffusion processes

no code implementations8 Jan 2016 David Schnoerr, Ramon Grima, Guido Sanguinetti

Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

Epidemiology Model Selection

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