Add Lang_PLOSComputBiol2024

[paulflang]

Is the readme up to date that you still welcome additional benchmark models? If so, I'd like to contribute this.

A few points to mention on this PR:

• The following works locally:

  >>> import benchmark_models_petab as models
  >>> problem = models.get_problem('Lang_PLOSComputBiol2024')
  >>> assert problem.measurement_df is not None

• petablint complains about using observables in the noiseFormula. saCeSS (and I believe parPE) did not have a problem with that. This can be changed but will be less concise.

  Missing parameter(s) in the model or the parameters table: {'obs_cycA__cyt_median', 'obs_p21__cyt_median', 'obs_cycE__nuc_median', 'obs_pRB__cyt_median', 'obs_p21__nuc_median', 'obs_cycA__nuc_median', 'obs_E2F1__cyt_median', 'obs_Skp2__nuc_median', 'obs_Skp2__cyt_median', 'obs_cycB1__cyt_median', 'obs_p27__cyt_median', 'obs_cycB1__nuc_median', 'obs_E2F1__nuc_median', 'obs_cycE__cyt_median', 'obs_p27__nuc_median', 'obs_pRB__nuc_median'}   
  Not OK

• The other models contain observable and noise parameter overrides in the measurement table, which is not needed in my case, but can be changed, too, of course.

• The SBML file contains the optimized parameters. I've never tried an optimization with this file, but I don't see a reason why it shouldn't work 🤞

• More generally, please lmk what else I need to do.

[dweindl]

Thanks Paul. Sorry for the late response. Contributions are still very welcome!

petablint complains about using observables in the noiseFormula. saCeSS (and I believe parPE) did not have a problem with that. This can be changed but will be less concise.

Right, it's supported by amici/parpe, but unfortunately not in PEtab v1 (https://github.com/PEtab-dev/PEtab/issues/543). Will be supported in the next PEtab version. I guess for now it would be better to substitute the observable IDs.

[paulflang]

Thanks @dweindl , I pushed the substitution.

[m-philipps]

Hi Paul, thank you for the contribution, it is very welcome!

I'm checking the model based on this checklist and already added the simulated data and updated the visualisation specification to match Figure 7 in your publication. Is that fine with you?

It would be great if you could provide some information on the points below in the corresponding issue #210

• [x] A brief model description (one or two sentences)
• [x] A brief data description (one or two sentences)
• [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)

and if you could check this point:

• [x] The model ID and model name attributes in the SBML model file match the problem name (example)

Thank you already!