The Computational Cancer Community (C3) was created to provide a forum for labs focused on cancer genomics and computational cancer biology and oncology to share their work and to get feedback and input.
More about the C3
The C3 community is a group of faculty, labs, and trainees that broadly fits within computational cancer research such as cancer genomics, computational cancer biology, and cancer data science. Learn more in this Q&A with Franklin Huang, MD, PhD:
The Computational Cancer Community (C3) is offering a six-week Computational Cancer Boot Camp.
The purpose of the Boot Camp is to introduce trainees to ideas in computational cancer including bioinformatics, computational biology, and statistics. As part of this process, we will teach the R language. After attending the Boot Camp, participants should be able to better advance their own computational cancer research, better interpret the computational cancer approaches of others, and program in the R language.
- R Programming sessions (Mission Bay + virtual): Every Tuesday and Thursday from 4-6pm between Oct 10 and Nov 9
- Scientific sessions (Mission Bay only): Daily from 9am-4pm between Nov 13 and Nov 17
Eligibility: Targeted towards postdocs and clinical fellows in cancer, but we encourage anyone associated with UCSF to apply
Registration: APPLY HERE by Sept 22, 2023 | Acceptances given by Sept 26, 2023
The C3 Boot Camp is targeted towards postdoctoral scholars and clinical fellows in cancer, but we encourage anyone associated with UCSF to apply. We are planning to expand our capacity this year to accommodate a larger group of students.
The R programming portion of the Boot Camp will be taught in hybrid format, with in-person attendance at UCSF Mission Bay strongly encouraged, every Tuesday and Thursday from 4-6pm between 10/10 and 11/9. The scientific portion of the Boot Camp will be held in person at Mission Bay from 9am-4pm between 11/13 and 11/17, with breakfast and lunch included. Mornings will include lectures from experts in the field covering the topics below, while afternoons will be focused on a week-long hands-on project.
- Statistics and analytic methods including batch effects adjustment, dimension reduction and clustering, and enrichment and pathway analysis
- Transcriptomics including bulk and single cell RNA-seq technology and analytic techniques
- Genomics including GWAS, whole genome sequencing, whole exome sequencing, and cancer panel studies
- Proteomics technologies, resources and network analysis
- State of the art talks from UCSF researchers
The Computational Cancer Boot Camp is free of charge to participants due to the generous sponsorship of the Helen Diller Family Comprehensive Cancer Center and the Bakar Computational Health Sciences Institute.
- Adam Olshen, PhD
- Alex Pico, PhD
- Ashir Borah
- Franklin Huang, MD PhD
- Karla Lindquist, PhD
- Scooter Morris, PhD