Team:UC San Diego/Contribution



Like other teams, this year’s UC San Diego iGEM team has struck with many adversities such as the pandemic, and consequently lack of membership and funding. However, despite the obstacles we encountered, we managed to produce a project with the following parts:

Developed a methodology to computationally determine individual tumor-suppressing microbes from RNA-sequencing data.

Submitted new parts to the Registry pages with documentation of various tumor-suppressing sequences.

Created a machine learning framework for future projects to use.

Formed a plan for future direction for in vitro validation via 3D Organoids.