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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

Benchmark-Models-PEtab

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. The publication for the introduction and analysis of the benchmark problem collection is available at https://academic.oup.com/bioinformatics/article/35/17/3073/5280731.

Contributions to the collection are very welcome. For this, please create a new branch, add your model and test your files with the provided functions, and start a pull request. We will then check your model and merge it into the collection. We are continuously working on the extension of the collection.

Overview

PEtab Problem ID Conditions Estimated Parameters Events Preequilibration Postequilibration Measurements Observables Noise distribution(s) Species References SBML4Humans
Alkan_SciSignal2018 73 56 0 0 0 1733 12 normal 36 [1] [1]
Bachmann_MSB2011 36 113 0 0 0 541 20 normal; log10-normal 25 [1] [1]
Beer_MolBioSystems2014 19 72 0 0 0 27132 2 normal 4 [1] [1]
Bertozzi_PNAS2020 2 3 0 0 0 138 1 normal 3 [1] [1]
Blasi_CellSystems2016 1 9 0 0 1 252 15 log-normal 16 [1] [1]
Boehm_JProteomeRes2014 1 9 0 0 0 48 3 normal 8 [1] [1]
Borghans_BiophysChem1997 1 23 0 0 0 111 1 log10-normal 3 [1] [1]
Brannmark_JBC2010 8 22 0 1 0 43 3 normal 9 [1] [1]
Bruno_JExpBot2016 6 13 0 0 0 77 5 normal 7 [1] [1]
Chen_MSB2009 4 155 0 0 0 120 3 normal 500 [1] [1]
Crauste_CellSystems2017 1 12 0 0 0 21 4 normal 5 [1] [1]
Elowitz_Nature2000 1 21 0 0 0 58 1 log10-normal 8 [1] [1]
Fiedler_BMC2016 3 22 0 0 0 72 2 normal 6 [1] [1]
Froehlich_CellSystems2018 9169 4231 0 0 9169 9169 1 normal 1396 [1] [1]
Fujita_SciSignal2010 6 19 0 0 0 144 3 normal 9 [1] [1]
Giordano_Nature2020 1 50 0 0 0 313 7 normal 13 [1] [1]
Isensee_JCB2018 123 46 0 1 0 687 3 normal 25 [1] [1]
Laske_PLOSComputBiol2019 3 13 0 0 0 42 13 normal; log-normal 41 [1] [2] [3] [1]
Lucarelli_CellSystems2018 16 84 0 0 0 1755 65 normal; log10-normal 33 [1] [1]
Okuonghae_ChaosSolitonsFractals2020 1 16 0 0 0 92 2 normal 9 [1] [1]
Oliveira_NatCommun2021 1 12 0 0 0 120 2 normal 9 [1] [1]
Perelson_Science1996 1 3 0 0 0 16 1 log10-normal 4 [1] [1]
Rahman_MBS2016 1 9 0 0 0 23 1 normal 7 [1] [1]
Raia_CancerResearch2011 4 39 0 0 0 205 8 normal 14 [1] "MedB-1 model" [1]
Raimundez_PCB2020 170 136 0 4 0 627 79 normal 22 [1] [1]
SalazarCavazos_MBoC2020 4 6 0 0 0 18 3 normal 75 [1] [1]
Schwen_PONE2014 19 30 0 0 0 286 4 log10-normal 11 [1] [1]
Smith_BMCSystBiol2013 35 25 3 0 0 62 9 normal 133 [1] [1]
Sneyd_PNAS2002 9 15 0 0 0 135 1 normal 6 [1] [1]
Weber_BMC2015 2 36 0 1 0 135 8 normal 7 [1] [1]
Zhao_QuantBiol2020 7 28 0 0 0 82 1 normal 5 [1] [1]
Zheng_PNAS2012 1 46 0 1 0 60 15 normal 15 [1] [1]

License

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

Installation

See INSTALL.md.

How to Cite

When using this work, please cite an appropriate version on Zenodo: https://doi.org/10.5281/zenodo.8155057

References

The model collection has been used in multiple publications.

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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Metadata

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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