Mishra_MetabEng2023

[mariesieger]

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
• [ ] 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
  • [x] Differences between the implementation and the original publication are described
  • [ ] Experience of fitting / uncertainty analysis (e.g. optimizer used, hyperparameters, reproducibility of best fit)
  • [ ] 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)
• [ ] PEtab files
  • [ ] A "simulated data" measurement table is included, using the nominal parameters
  • [x] ~~A visualization table is included, that can be used with the simulated data to reproduce figures from the original publication~~ script to reproduce the papers figure can be found in the README.md
  • [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 bmp-create-overview --update (requires pip install -e src/python/bmp from the repository root)
  • [x] The new PEtab problem row in the generated table has the correct reference (and other entries)