Web Development
SciDash
Technologies
Django ReactJS DRF celery Redis SciUnit NeuronUnit
scientific dashboard for model validation
Both software developers and neuroscientists actually face the same problems: they must understand the scope of each component of a complex project and verify that each component achieves the desired input/output behavior.
So, the professor from the University of Arizona required a platform to manage his libraries for testing the scientific models he was working on.
Process
We actually built an output table with the possibility to test different scientific models and visualize the results. The dashboard is responsible for the validation of scientific models against experimental data. It helps understand how accurate the model is using the Python framework SciUnit and the extensible NeuronUnit library for neuron testing.
Features:
1. Test scores;
2. Models dashboard with the following model features:
- name;
- source URL;
- class;
- instance;
- tags.
3. A dashboard to run scientific tests;
4. Suite scores;
5. Tests scheduling.
Result
SciDash aims to make validation of computational scientific models against experimental data easy, transparent, and continuously integrated into the model development process.” The non-profit project is of practical use for university professors who work on reproducible execution and visualization of data-driven unit tests for assessing model quality. It is a 21st-century vision of the scientific method.
See project
Team
Full-Stack Developer
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