A collection of mathematical models with experimental data in the PEtab format as benchmark problems in order to evaluate new and existing methodologies for data-based modelling
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Bertozzi_PNAS2020: update to match Table 1 of paper #222
I also changed the problem to be a simple SIR model, instead of the reparameterized SIR, but the reparameterization parameters are used in the parameters table, s.t. users can compare their parameter estimates to Table 1 of the original publication. The reparameterization is implemented as an SBML initial assignment rule $\beta = \frac{R_0 \gamma}{N}$.
I also removed some features like lockdown events, since they are irrelevant for reproducing the figure in Table 1 but complicate the simulation.
The scripts were updated to use petab.v1 and support output from petab.Problem.to_files_generic.
Checklist for the submission of new PEtab problems
[X] The PEtab problem is based on a model that is peer-reviewed and published
[X] The problem ID is in the format {LAST_NAME_OF_FIRST_AUTHOR}_{ABBREVIATED_JOURNAL_NAME}{YEAR_OF_PUBLICATION}
[X] The problem ID is in the pull request title
[X] There is a GitHub issue for this problem
[X] The problem ID is in the issue title
[X] A brief model description (one or two sentences)
[X] A brief data description (one or two sentences)
[X] The issue and PR are linked to each other (#99)
[X] Differences between the implementation and the original publication are described
[X] Experience of fitting / uncertainty analysis (e.g. optimizer used, hyperparameters, reproducibility of best fit)
[X] Source of nominal parameters (e.g.: taken from the original publication, or from your own fitting)
[X] The SBML file
[X] Annotation with reference to the original publication (example)
[X] The model ID and model name attributes in the SBML model file match the problem name (example)
[X] PEtab files
[X] A "simulated data" measurement table is included, using the nominal parameters
[X] A visualization table is included, that can be used with the simulate data to reproduce figures from the original publication
[X] The PEtab problem is valid (check with e.g. petablint -vy problem.yaml)
[X] The PEtab problem author(s) are assigned to the GitHub issue
[X] The README has been updated with python scripts/overview.py --update
[X] The new PEtab problem row in the generated table has the correct reference (and other entries)
Some details in #99
I also changed the problem to be a simple SIR model, instead of the reparameterized SIR, but the reparameterization parameters are used in the parameters table, s.t. users can compare their parameter estimates to Table 1 of the original publication. The reparameterization is implemented as an SBML initial assignment rule $\beta = \frac{R_0 \gamma}{N}$.
I also removed some features like lockdown events, since they are irrelevant for reproducing the figure in Table 1 but complicate the simulation.
The scripts were updated to use
petab.v1
and support output frompetab.Problem.to_files_generic
.Checklist for the submission of
newPEtab problems{LAST_NAME_OF_FIRST_AUTHOR}_{ABBREVIATED_JOURNAL_NAME}{YEAR_OF_PUBLICATION}
petablint -vy problem.yaml
)python scripts/overview.py --update