README.md

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. Please see CONTRIBUTING.md for more details.

Overview

PEtab Problem ID	Conditions	Estimated Parameters	Events	Possible Discontinuities	Preequilibration	Postequilibration	Measurements	Observables	Noise distribution(s)	Objective prior distribution(s)	Species	References	SBML4Humans
Alkan_SciSignal2018	73	56	0	✓	0	0	1733	12	normal		36	[1]	[1]
Armistead_CellDeathDis2024	2	14	0		0	0	58	4	normal		4	[1]	[1]
Bachmann_MSB2011	36	113	0		0	0	541	20	normal; log10-normal	parameterScaleNormal	25	[1]	[1]
Beer_MolBioSystems2014	19	72	0	✓	0	0	27132	2	normal		4	[1]	[1]
Bertozzi_PNAS2020	2	8	0		0	0	22	2	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_BMCSystBiol2016	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	parameterScaleNormal	25	[1]	[1]
Lang_PLOSComputBiol2024	1	294	0		0	0	9600	16	normal	laplace; uniform	124	[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]	[1]
Raimundez_PCB2020	170	136	0	✓	4	0	627	79	normal	parameterScaleNormal; laplace	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	parameterScaleNormal	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

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 Zenodo year and version 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 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.