Mira
Overview
MIRA is a framework for representing systems using ontology-grounded meta-model templates, and generating various model implementations and exchange formats from these templates. It also implements algorithms for assembling and querying domain knowledge graphs in support of modeling.
Target Users:
Mira can be used by modelers or researchers who want to transform or extend an existing model in various ways, to meet the needs of their specific situation.
Features Supported:
Users can use Mira to:
- Make structural model modifications
- Do structural model comparison for model selection purposes
- Extend existing domain knowledge graphs (DKGs) or add new DKGs, for models being applied to new contexts
Resources
- Template JSON schema: schema.json
- Epidemiology Domain Knowledge Graph (DKG) service: DKG service
- MIRA Metaregistry service: Metaregistry service
Installation and Configuration
The most recent code and data can be installed directly from GitHub with:
python -m pip install git+https://github.com/gyorilab/mira.git
To install in development mode, use the following:
git clone git+https://github.com/gyorilab/mira.git
cd mira
python -m pip install -e .
The dependencies for the project are listed in the top-level configuration file setup.cfg.
If you wanted to install extra dependencies that aren’t listed under install_requires in setup.cfg, such as the packages required for running ode simulations, use the following:
python -m pip install -e .[ode]
To install multiple dependency blocks listed in setup.cfg, run the following:
python -m pip install -e .[ode,docs]
Extra dependency blocks/packages required for modules
| Module | Dependency |
|---|---|
mira/modeling/ode.py | ode |
mira/modeling/viz.py | viz |
mira/sources/biomodels.py | biomodels |
mira/sources/sbml/processor.py | sbml |
mira/sources/space_latex.py | tests |
Documentation
Full documentation can be found here.
Example Notebooks
- Defining multiple model variants using MIRA Templates: Notebook 1
- Generating an executable model from MIRA Templates and running simulation: Notebook 2
- Stratifying and visualizing MIRA models, and exporting as Petri nets: Notebook 3
- Processing an SBML model from BioModels, visualizing and exporting into Petri nets: Notebook 4
- Using the MIRA Domain Knowledge Graph REST API: Notebook 5
- Using the Model REST API to perform various model operations: Notebook 6
- Using the web client in python that connects to the REST API: Notebook 7
- Demonstrating MIRA TemplateModel capabilities Notebook 8
- Rapid construction of DKGs in ASKEM: Notebook 9
- Implement a masking intervention in a compartmental model to simulate epidemic trajectories under different scenarios: Notebook 10
- Benchmarking the efficacy of DKG groundings on a set of COVID EPI Models: Notebook 11