More comprehensive and more predictive models have the potential to advance biology, bioengineering, and medicine. Building more predictive models will likely require the collaborative efforts of many investigators. This requires teams to be able to share and reuse model components and modeling tools. Despite extensive efforts to develop standards such as the COMBINE/OMEX archive format, the Kinetic Simulation Algorithm Ontology (KiSAO), the Systems Biology Markup Language (SBML), and the Simulation Experiment Description Markup Language (SED-ML) and repositories such as BioModels and the Physiome Model Repository, it is still often difficult to share, reuse, and combine models and modeling tools. One challenge to sharing and reusing models is the disparate formats, model repositories, and simulation tools for different types of models. The proliferation of numerous similar formats, repositories, and tools makes it difficult, especially for non-experts, to find models and to find an appropriate simulation tool for each model. In addition, the existing model repositories have limited capabilities for sharing associated resources such as training data, simulation experiments, and visualizations. BioSimulators addressses these challenges by making it easier for researchers to share and reuse modeling tools.
- Home page: https://biosimulators.org
- REST API: https://api.biosimulators.org
- Docker images: https://github.com/orgs/biosimulators/packages
- Command-line programs: https://pypi.org/user/biosimulators
- Python APIs: https://pypi.org/user/biosimulators
- Tutorials: https://tutorial.biosimulators.org
- Documentation: https://docs.biosimulations.org
- Example simulation projects: https://github.com/biosimulators/Biosimulators_test_suite/tree/dev/examples
- Template for simulation tools: https://github.com/biosimulators/Biosimulators_simulator_template