FAQ

1. How to set up a DALSP model?

• Basics
  • M.type - Dependencies of the rates of cell division and cell death, i.e. 'constant', 'age-dependent', 'time-dependent' and 'time- and age-dependent'.
  • M.time - Symbolic variable for time.
  • M.age - Symbolic variable for cell age.
  • M.name - String for the model name.
  • M.S - Maximum number of cell divisions.
• Initial age distribution
  • M.IC.na0.int - Integral over initial age distribution.
  • M.IC.na0.type - Type of the initial distribution, i.e., 'delta' or 'log-normal'.
  • M.IC.na0.mu_fun - Location parameter of log-normal age distribution.
  • M.IC.na0.sigma_fun - Scale parameter of log-normal age distribution.
• Initial CFSE distribution
  • M.IC.px0.int - Integral over initial age distribution (usually = 1).
  • M.IC.px0.mu - Location parameter of log-normal distribution.
  • M.IC.px0.sigma - Scale parameter of log-normal distribution.
• Rates of cell division and cell death
  • M.alpha{i} - Rate of cell division for cells with i divisions.
  • M.beta{i} - Rate of cell death for cells with i divisions.
  • M.gamma - Dilution factor at division (usually = 1).
• CFSE degradation (k(t) = kexp(-ct))
  • M.degradation.k - Maximum degration rate.
  • M.degradation.c - Rate of degradation rate reduction.
• Background fluorescence
  • M.noise.mu - Location parameter of log-normal background distribution.
  • M.noise.sigma - Scale parameter of log-normal background distribution.
• Measurement noise for overall cell number
  • M.noise_N.sigma - Standard deviation of measurement noise.

2. What are the most important functions of ShAPE-DALSP?

• getDALSPmodel.m - Function converting a symbolically defined DALSP models in a series of numerical functions. The evaluation of these functions provides for examples the rate of cell division and its derivative with respect to the model parameters.
• CPsimulateDALSP.m - Function computing the solution to a division-, age- and label-structured population model for a given set of model parameters.
• plotProliferationAssay.m - Visualization routine for measured and simulated CFSE time-series data.
• logLikelihood_proliferation.m - Function evaluating the likelihood of a measured CFSE time-series data for a given parameter vector.

3. What are the most important functions of PESTO?

• getMultiStarts.m- Function computing the optima of the parameters of a user-supplied posterior function. Therefore, multi-start local optimization is used.
• getParameterProfiles.m- Function computing the profiles of a user-supplied function, starting from the maximum a posteriori estimate.
• getPropertySamples.m- Function performing a Bayesian uncertainty analysis using, e.g. adaptive MCMC sampling.