gillespie-type algorithm Search Results


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Expression data of the reporter gene of B. subtilis . Fluorescent protein expression scales linearly with cell length ( A ) and cell age ( B ), but the correlation is weaker for age. By transforming the extant length (Fig. ) and age (Fig. ) distributions with the linear relation between length and fluorescence and between age and fluorescence, respectively, predictions of the fluorescent distribution can be made. The result clearly shows that cell length ( C , dashed line) is a much better predictor of measured expression levels ( C , blue area), than age ( C , solid line). Also shown, is the distribution of expression levels obtained by <t>stochastic</t> simulation ( C , gray line). Measured fluorescence distributions at ( D ) birth and ( E ) division (blue areas) are compared to stochastic simulations (gray lines). ( F ) Shows the comparison of the measured distribution of the fluorescence concentration of all extant cells (blue) and the simulations (gray line).
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Expression data of the reporter gene of B. subtilis . Fluorescent protein expression scales linearly with cell length ( A ) and cell age ( B ), but the correlation is weaker for age. By transforming the extant length (Fig. ) and age (Fig. ) distributions with the linear relation between length and fluorescence and between age and fluorescence, respectively, predictions of the fluorescent distribution can be made. The result clearly shows that cell length ( C , dashed line) is a much better predictor of measured expression levels ( C , blue area), than age ( C , solid line). Also shown, is the distribution of expression levels obtained by stochastic simulation ( C , gray line). Measured fluorescence distributions at ( D ) birth and ( E ) division (blue areas) are compared to stochastic simulations (gray lines). ( F ) Shows the comparison of the measured distribution of the fluorescence concentration of all extant cells (blue) and the simulations (gray line).

Journal: Scientific Reports

Article Title: Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli

doi: 10.1038/s41598-017-15895-4

Figure Lengend Snippet: Expression data of the reporter gene of B. subtilis . Fluorescent protein expression scales linearly with cell length ( A ) and cell age ( B ), but the correlation is weaker for age. By transforming the extant length (Fig. ) and age (Fig. ) distributions with the linear relation between length and fluorescence and between age and fluorescence, respectively, predictions of the fluorescent distribution can be made. The result clearly shows that cell length ( C , dashed line) is a much better predictor of measured expression levels ( C , blue area), than age ( C , solid line). Also shown, is the distribution of expression levels obtained by stochastic simulation ( C , gray line). Measured fluorescence distributions at ( D ) birth and ( E ) division (blue areas) are compared to stochastic simulations (gray lines). ( F ) Shows the comparison of the measured distribution of the fluorescence concentration of all extant cells (blue) and the simulations (gray line).

Article Snippet: StochPy has basic stochastic simulation algorithms (i.e. of the ‘Gillespie-type’), is readily extendible by the user, uses command-line instructions, allows for coding and saving of models in scripts, has a suite of statistical analysis and plotting tools, is compliant with SBML and can exchange models with the multi-purpose, deterministic modeling software package PySCeS ( http://pysces.sourceforge.net ) for systems biology.

Techniques: Expressing, Fluorescence, Comparison, Concentration Assay