Computational & Bench Scientist Ecosystem (CoBE)

Transforming data into discoveries.

CoBE’s Aims

  • Improve the reach and usage of computational tools
  • Empower bench scientists to confidently run analysis on biological data
  • Bridge the gap between the software creator and the software user

Barriers to data discovery 

As cancer research continues to rely on generation and analysis of big data. In recent years, the Princess Margaret Cancer Centre has made it possible for bench scientists to generate big data. For many reasons, computational analysis is crucial to make sense of biological data. Computational analysis is necessary to produce statistical analysis and data visualizations to test and validate hypotheses and present findings in a reproducible and standardized way. 

Therefore, the collaboration between computational and bench scientists is essential for making progress in biological data discovery. 

How can CoBE help? 

CoBE has 5 core features. 


No registration or login required to start exploring tools and pipelines. Register your UHN or Google account to gain access to the Build feature.  

Anyone logging in with a UHN account can take advantage of additional features. Go to the Execute section to learn more.  


Search through CoBE’s growing library of over 9000 tools and 22 complete pipelines analyzing 13 different data types with contributions by 13 different research groups.  

Publish your software in CoBE today, using the new and improved Build feature.  


Software creators can build software schematics as computational resources in the form of a tree diagram using CoBE’s new user-friendly interface.  

Build complete software pipelines using existing tools available in the CoBE library or create new tools.  

Tools within a pipeline will contain important metadata like tool purpose, input/output file types, external links to code repositories, executable links, and other related resources. 

Benefits to the software creator: 

  • Increases accessibility and visibility of software 
  • Promotes transparency 
  • Supports reproducibility 
  • Improves software reach and impact 


Tools and pipelines can be executed depending on the documentation provided. The CoBE library includes tools and pipelines with executable links to GitHub, third-party web applications, and Code Ocean. 

GitHub executable links can include code repositories and other important information and require expertise to set up and maintain local environments.  

Web application executable links can facilitate software execution, but additional costs may apply to run analysis. 

Code Ocean executable links provided a gold-standard software package and facilitates software execution in an easy-to-use interface allowing users to focus on reproducing results and less on the nuances of computational analysis.  

Code Ocean offers a free version where anyone can execute tools for free. UHN staff gain exclusive access to execute complete pipelines with more compute time and storage than the public option.  


Found software that helped with your data analysis? Hit the like button to highlight your favorite tools and pipelines, improve visibility, promote trust, and support the computational and bench scientist community! 

Additional Information

In 2021, CoBE was launched at the Princess Margaret Cancer Centre by Dr. Mathieu Lupien and Dr. Benjamin Haibe-Kains.

CoBE is the 2023-24 Princess Margaret Grand Challenge: Scalability winning project. The Grand Challenge competition offers support from the Cancer Digital Intelligence (CDI) program in front-end and back-end development, data science, design, and project management.

CoBE is undergoing a stunning redesign to enhance functionality and user experience. We are excited to onbaord beta testers for the first time! If you are interested in helping us improve the system, please contact

This project is a collaboration between the Mathieu Lupien Lab, BHK Lab, and the CDI Program. Team members: Dr. Mathieu Lupien and Dr. Benjamin Haibe-Kains, Matthew Boccalon, Ankita Nand, Benjamin Grant, Sharon Narine, Anton Sukhovatkin, Mickey Ng, Pietro Andreoli, Daniel Garcia, Srimathi Jayasimman, Kage Gamis, and Adam Badzynski.

Click here to learn more about the Lupien Lab.

Click here to learn more about the BHK Lab.

Click here to learn more about the Cancer Digital Intelligence (CDI) program.