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Figure 3A illustrates the initial distribution for a simulation initialised with 20,000 simulated cells.
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To model a well-adapted population, each simulation is initialised so that all non-synonymous changes from the ancestral sequence are negatively selected, reducing fitness by a factor of 1− s d.
Each simulation is initialised with a haploid population of N=10monomorphic individuals.
The simulation was initialised with a single bacterial host and perfect-match infectious phage (with genotype h init = v init =0.2) and run for a duration of T=20×10 min. Simulation parameters are given in Table 1.
To estimate the posterior distribution for each model, two Markov chain Monte Carlo simulations were initialised using 27 000 iterations for each simulation.
The simulations were initialised by placing either 20,000 or 30,000 simulated cells inside a circle located at the centre of the lattice.
Simulations were initialised with the species occupying 20% of the landscape and run for 100 years.
Simulations were initialised with a vessel surrounded by a thin layer of proliferating cells.
All of the stochastic simulations were initialised in the same state and behaved identically until a force is applied.
Simulations are initialised with a single bacterial population and infectious phage, then integrated forward for T minutes using a 4th order Runge-Kutta method with timestep Δt.
Simulations are initialised with h init = v init =0.2 in each case; the only parameter difference is the initial density of phage (set to V init =0 for the no-phage case).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com