Putting machine learning in the hands of cancer biologists.
Project Cognoma is an open source project to create a webapp for analyzing cancer data. We're a community-driven philanthropic project that began as a collaboration between the Greene Lab, DataPhilly, and Code for Philly. Our contributors are primarily based in the Philadelphia area, but anyone anywhere is welcome. This GitHub repository is the administrative and informational home of Cognoma.
The Meetup phase of Cognoma is now complete! The Childhood Cancer Data Lab of Alex's Lemonade Stand Foundation will be providing longterm maintenance. Public contributions are still welcome through GitHub. The main priority is enhancements and bug fixes to improve http://cognoma.org. For a nice overview of the project, see its coverage by The Philadelphia Citizen.
The project is composed of four teams with their own corresponding repositories:
| Team Name | Repositories | Description |
|---|---|---|
| Cancer Data | cancer-data, genes, figshare |
processing the underlying cancer data to the formats required for this project. |
| Machine Learning | machine-learning, cognoml |
building classifiers to predict mutation status from gene expression data. |
| Backend | core-service, task-service, ml-workers, infrastructure |
creating the infrastructure to power the webapp and glue the components together. |
| Frontend | frontend, uiux |
building the webapp that users interact with. |
If you are a new user and would like to get involved, please introduce yourself.
Contributions are made through GitHub, so if you are unfamiliar with git or GitHub, check out the sandbox for a place to learn by doing.
We hold project meetups. Our usual meeting spot is at Industrious (where CandiDate is located). The address is 230 S Broad St, Floor 17, Philadelphia.
Community contributions are the driving force behind Cognoma. The heatmap below shows which users have contributed to which repositories:
See the guidelines for contributing for more information.
Cognoma relies on our generous community maintainers to assist with contributions. Thanks to the following maintainers for their help:
- Cancer Data: Claire McLeod (@clairemcleod)
- Machine Learning: Patrick Miller (@patrick-miller), Ryan Velazquez (@rdvelazquez), Jesse Prestwood-Taylor (@jessept), Yichuan Liu (@yl565)
- Backend: Derek Goss (@dcgoss), Andrew Madonna (@awm33), Kurt Wheeler (@kurtwheeler)
- Frontend: Benjamin Dolly (@bdolly)
- Community: Karin Wolok (@KarinSpiderwoman)
- Wildcards: Daniel Himmelstein (@dhimmel), Gregory Way (@gwaygenomics), Casey Greene (@cgreene)
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