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)