sbmlsim: SBML simulation made easy
sbmlsim is a collection of python utilities for the simulation of models in the Systems Biology Markup Language (SBML), built on libroadrunner.
Features include
- timecourse simulations - concatenated timecourses with changes of parameters and initial conditions, in the units of the model
- parameter scans - simulations over dimensions of values, simulations and models, serially or in a pool of processes, with results as labeled N-dimensional arrays with units (xarray)
- simulation experiments - models, datasets, simulations, tasks and figures of an experiment as one reproducible python object, with HTML and markdown reports
- parameter fitting - optimization problems from experimental data with local and global optimizers, and PEtab archives
- sensitivity analysis - local sensitivities and the global Morris, Sobol and FAST methods
The documentation is available at https://matthiaskoenig.github.io/sbmlsim.
If you have any questions or issues please open an issue.
How to cite
If you use sbmlsim please cite the archived software on Zenodo:
König, M. (2026). sbmlsim: SBML simulation made easy (Version 0.9.2) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.23309677
@software{konig_sbmlsim,
author = {König, Matthias},
title = {sbmlsim: SBML simulation made easy},
year = {2026},
month = oct,
version = {0.9.2},
publisher = {Zenodo},
doi = {10.5281/zenodo.23309677},
url = {https://doi.org/10.5281/zenodo.23309677},
}
License
- Source Code: MIT
- Documentation: CC BY-SA 4.0
Funding
Matthias König is supported by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151 "QuaLiPerF (Quantifying Liver Perfusion-Function Relationship in Complex Resection - A Systems Medicine Approach)" by grant number 436883643 and by grant number 465194077 (Priority Programme SPP 2311, Subproject SimLivA).
Matthias König was supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054). Matthias König has received funding from the EOSCsecretariat.eu which has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.
© 2019-2026 Matthias König, https://livermetabolism.com
1 maintainer
Metadata
1 maintainer
Release files for sbmlsim 0.9.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sbmlsim-0.9.3.tar.gz | 2.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sbmlsim-0.9.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.7 MB
Release files / sbmlsim-0.9.3.tar.gz
| Download URL | sbmlsim-0.9.3.tar.gz |
|---|---|
| Size | 2.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
17a6b80288ff4a861f895222a4ebbc0cbca35ad4f571d5ed10d3701871815e42
|
|
BLAKE2b-256 checksum How to use checksums |
b69374318f83a66dde879fda123b93a69c84e2437a46b08199d72eb432b2d9db
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 12, 2026.
Transparency logRelease files / sbmlsim-0.9.3-py3-none-any.whl
| Download URL | sbmlsim-0.9.3-py3-none-any.whl |
|---|---|
| Size | 643.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
63c0025f36484b6245525200ba627cd876d7113e2173a0a2dcb56a278b37275c
|
|
BLAKE2b-256 checksum How to use checksums |
b17f83e168a5a378f9b146d8b8634a592a441546293f9acd7f28454915c5a1d9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 12, 2026.
Transparency log
