Holimap: an accurate and efficient method for solving stochastic gene network dynamics
Gene-gene interactions are crucial to the control of sub-cellular processes but our
understanding of their stochastic dynamics is hindered by the lack of simulation methods …
understanding of their stochastic dynamics is hindered by the lack of simulation methods …
Concentration fluctuations in growing and dividing cells: Insights into the emergence of concentration homeostasis
Intracellular reaction rates depend on concentrations and hence their levels are often
regulated. However classical models of stochastic gene expression lack a cell size …
regulated. However classical models of stochastic gene expression lack a cell size …
Approximating solutions of the chemical master equation using neural networks
Summary The Chemical Master Equation (CME) provides an accurate description of
stochastic biochemical reaction networks in well-mixed conditions, but it cannot be solved …
stochastic biochemical reaction networks in well-mixed conditions, but it cannot be solved …
Coupling gene expression dynamics to cell size dynamics and cell cycle events: Exact and approximate solutions of the extended telegraph model
The standard model describing the fluctuations of mRNA numbers in single cells is the
telegraph model which includes synthesis and degradation of mRNA, and switching of the …
telegraph model which includes synthesis and degradation of mRNA, and switching of the …
Gene expression model inference from snapshot RNA data using Bayesian non-parametrics
Gene expression models, which are key towards understanding cellular regulatory
response, underlie observations of single-cell transcriptional dynamics. Although RNA …
response, underlie observations of single-cell transcriptional dynamics. Although RNA …
Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number
Identifying the sources of cell-to-cell variability in signaling dynamics is essential to
understand drug response variability and develop effective therapeutics. However, it is …
understand drug response variability and develop effective therapeutics. However, it is …
Quantifying and correcting bias in transcriptional parameter inference from single-cell data
R Grima, PM Esmenjaud - Biophysical Journal, 2024 - cell.com
The snapshot distribution of mRNA counts per cell can be measured using single-molecule
fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are …
fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are …
Cell size distribution of lineage data: analytic results and parameter inference
Recent advances in single-cell technologies have enabled time-resolved measurements of
the cell size over several cell cycles. These data encode information on how cells correct …
the cell size over several cell cycles. These data encode information on how cells correct …
[HTML][HTML] Solving the time-dependent protein distributions for autoregulated bursty gene expression using spectral decomposition
In this study, we obtain an exact time-dependent solution of the chemical master equation
(CME) of an extension of the two-state telegraph model describing bursty or non-bursty …
(CME) of an extension of the two-state telegraph model describing bursty or non-bursty …
Analytical time-dependent distributions for gene expression models with complex promoter switching mechanisms
Classical gene expression models assume exponential switching time distributions between
the active and inactive promoter states. However, recent experiments have shown that many …
the active and inactive promoter states. However, recent experiments have shown that many …