Browse Models
Learn how to effectively search and discover biological models in the Biosimulant catalog.
Time estimate: 10 minutes
Goal
By the end of this tutorial, you’ll be able to:
- Search for models by name and keyword
- Filter models by standard and catalog metadata
- Understand the key metadata exposed on a model page
- Open a model in a lab and continue from there
The Model Browser
Navigate to Models in the top navigation to access the model browser.
Search Bar
The search bar supports:
- Model names: “Lotka-Volterra”, “Glycolysis”
- Keywords: “cancer”, “metabolism”, “signaling”
- Repository slugs: “demo/mapk-cascade”
Start with a broad keyword, then narrow with filters. The exact search grammar may vary across product tiers or workspaces.
Filtering Models
By Model Standard
- SBML: Systems Biology Markup Language - biochemical pathway models
- NeuroML: Neural models for computational neuroscience
- CellML: Physiological models for cell biology
- NMODL: NEURON MOD files for neural simulation
- ONNX: Machine learning models for hybrid simulations
By Catalog Metadata
- Tags: domain labels, curation labels, or workflow labels
- Visibility/source: public catalog versus items attached to your account, when exposed
- Recently updated or similar sort orders, when exposed by the UI
Model Details
Click on any model to see:
Overview Tab
- Description: What the model represents
- Package identity: Package name and version, if present
- Standard: SBML, NeuroML, ONNX, or other
- Tags and metadata: Public discovery fields attached to the model
Package and Interface Details
- Entrypoint or packaged artifact details
- Declared parameters or configurable module inputs, when available
- Manifest-backed metadata from the package or linked repository
Versions and Linked Assets
- Current version and update history, when versioning is enabled
- Source repository or upload provenance, when available
- Labs using this model, when the UI exposes related labs
Opening a Model in a Lab
- Open the model detail page
- Choose Open in Lab or the equivalent action in your UI
- Review the generated or linked lab configuration
- Start a run or save the lab for later
Best Practices
- Start broad, then narrow: Begin with general terms, add filters as needed
- Check package metadata: Model quality varies; versioned and clearly described packages are easier to trust
- Open the lab before running: This makes it easier to inspect defaults and overrides
- Compare related models: Multiple models may represent the same system differently
Next Steps
- Run a Simulation - Execute a model you’ve found
- Biosimulant Library - Work with models in Python