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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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Benchmarking-Initiative/Benchmark-Models-PEtab

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A collection of mathematical models with experimental data in thePEtab format as benchmark problems in order to evaluate new and existing methodologies for data-based modelling. The publication for the introduction and analysis of the benchmark problem collection is available athttps://academic.oup.com/bioinformatics/article/35/17/3073/5280731.

Contributions to the collection are very welcome. Please seeCONTRIBUTING.md for more details.

Overview

The following table summarizes the problems in the collection.The full set of PEtab files are available in the respective subfolders.A sortable version of the table is availablehere.

PEtab Problem IDConditionsEstimated ParametersEventsPossible DiscontinuitiesPreequilibrationPostequilibrationMeasurementsObservablesNoise distribution(s)Objective prior distribution(s)SpeciesReferencesSBML4Humans
Alkan_SciSignal201873560✓00173312normal36[1][1]
Armistead_CellDeathDis2024214000584normal4[1][1]
Bachmann_MSB20113611300054120normal; log10-normalparameterScaleNormal25[1][1]
Beer_MolBioSystems201419720✓00271322normal4[1][1]
Bertozzi_PNAS202028000222normal3[1][1]
Blasi_CellSystems20161900125215log-normal16[1][1]
Boehm_JProteomeRes201419000483normal8[1][1]
Borghans_BiophysChem19971230001111log10-normal3[1][1]
Brannmark_JBC20108220✓10433normal9[1][1]
Bruno_JExpBot2016613000775normal7[1][1]
Chen_MSB200941550✓001203normal500[1][1]
Crauste_CellSystems2017112000214normal5[1][1]
Elowitz_Nature2000121000581log10-normal8[1][1]
Fiedler_BMCSystBiol2016322000722normal6[1][1]
Froehlich_CellSystems20189169423100916991691normal1396[1][1]
Fujita_SciSignal20106190✓001443normal9[1][1]
Giordano_Nature20201500✓003137normal13[1][1]
Isensee_JCB2018123460✓106873normalparameterScaleNormal25[1][1]
Lang_PLOSComputBiol20241294000960016normallaplace; uniform124[1][1]
Laske_PLOSComputBiol20193130004213normal; log-normal41[1][2][3][1]
Lucarelli_CellSystems20181684000175565normal; log10-normal33[1][1]
Okuonghae_ChaosSolitonsFractals2020116000922normal9[1][1]
Oliveira_NatCommun20211120✓001202normal9[1][1]
Perelson_Science199613000161log10-normal4[1][1]
Rahman_MBS201619000231normal7[1][1]
Raia_CancerResearch20114390002058normal14[1][1]
Raimundez_PCB20201701360✓4062779normalparameterScaleNormal; laplace22[1][1]
SalazarCavazos_MBoC202046000183normal75[1][1]
Schwen_PONE201419300002864log10-normalparameterScaleNormal11[1][1]
Smith_BMCSystBiol201335253✓00629normal133[1][1]
Sneyd_PNAS20029150001351normal6[1][1]
Weber_BMC20152360✓101358normal7[1][1]
Zhao_QuantBiol2020728000821normal5[1][1]
Zheng_PNAS20121460106015normal15[1][1]

License

Any original content in this repository may be used under the terms of theBSD-3-Clause license.Different terms may apply to models and datasets, for which we refer the user to the original publicationsthat are referenced in the respective SBML files.

Installation

SeeINSTALL.md.

How to Cite

Please cite the benchmark collection by citing:

  1. the PEtab paper, which first introduced this collection in a peer-reviewed publication:https://doi.org/10.1371/journal.pcbi.1008646
  2. the Zenodo repository, where you can cite specific versions of the files:https://doi.org/10.5281/zenodo.8155057

Example BibTeX (customize the Zenodoyear andversion to match your version):

@misc{petab_benchmark_collection,author       ={The PEtab Benchmark Collection contributors},title        ={{The PEtab Benchmark Collection of parameter estimation problems}},year         =2024,publisher    ={Zenodo},version      ={2024.10.15},doi          ={10.5281/zenodo.8155057},url          ={https://doi.org/10.5281/zenodo.8155057}}@article{petab,doi ={10.1371/journal.pcbi.1008646},author ={Schmiester, Leonard AND Schälte, Yannik AND Bergmann, Frank T. AND Camba, Tacio AND Dudkin, Erika AND Egert, Janine AND Fröhlich, Fabian AND Fuhrmann, Lara AND Hauber, Adrian L. AND Kemmer, Svenja AND Lakrisenko, Polina AND Loos, Carolin AND Merkt, Simon AND Müller, Wolfgang AND Pathirana, Dilan AND Raimúndez, Elba AND Refisch, Lukas AND Rosenblatt, Marcus AND Stapor, Paul L. AND Städter, Philipp AND Wang, Dantong AND Wieland, Franz-Georg AND Banga, Julio R. AND Timmer, Jens AND Villaverde, Alejandro F. AND Sahle, Sven AND Kreutz, Clemens AND Hasenauer, Jan AND Weindl, Daniel},journal ={PLOS Computational Biology},publisher ={Public Library of Science},title ={PEtab—Interoperable specification of parameter estimation problems in systems biology},year ={2021},month ={01},volume ={17},url ={https://doi.org/10.1371/journal.pcbi.1008646},pages ={1-10},abstract ={Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been—so far—no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies.},number ={1},}

References

The model collection has been used in multiplepublications.

If you used the benchmark problems in your work and your publication is missing, please let us know via a new GitHub issue.

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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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