https://github.com/vjcitn/biocyes
Software for CZI project on Bioconductor diversity and inclusiveness with DFCI YES for CURE
https://github.com/vjcitn/biocyes
Last synced: 4 months ago
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Software for CZI project on Bioconductor diversity and inclusiveness with DFCI YES for CURE
- Host: GitHub
- URL: https://github.com/vjcitn/biocyes
- Owner: vjcitn
- Created: 2022-02-21T01:04:23.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-04-07T20:44:18.000Z (about 3 years ago)
- Last Synced: 2025-01-09T13:46:36.743Z (5 months ago)
- Language: Jupyter Notebook
- Size: 7.6 MB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# BiocYES
The BiocYES R package defines
software and documentation for a [Chan-Zuckerberg Initiative
project](https://chanzuckerberg.com/eoss/proposals/bioconductor-sustaining-a-worldwide-community-of-genome-data-scientists/)
on Bioconductor's diversity and inclusiveness with [DFCI YES for CURE](https://www.dfhcc.harvard.edu/research/cancer-disparities/students/yes-for-cure/).
Our primary concern is to develop open resources for training high school and undergraduate students in cancer data science.
Here's a very recent comment published in the [Harvard Gazette](https://news.harvard.edu/gazette/story/2022/03/bringing-the-cancer-fight-back-down-to-earth), to help motivate interest
in data science for cancer research:
*They (Drs Karen Emmons, George Demetri, and Timothy Rebbeck) agreed, however, that one of the project’s chief objectives — halving the cancer death rate — is possible. Optimism stems from dramatic advances over the past two decades in understanding cancer biology, which has translated into more effective treatments. These breakthroughs include precision therapies, which target specific differences between tumor and normal cells in individual patients, and immunotherapy, which activates the body’s defense mechanisms against the disease.*
*“These new classes of treatments are the two big lessons of the last 20 years, and those are pretty remarkable,” said George Demetri, a professor of medicine at Harvard Medical School and the Dana-Farber Cancer Institute and co-director of the Ludwig Center at Harvard. “And I can guarantee you that there’ll be at least two more big ones in the next 20 years.”*
*Demetri gives the original moonshot a mixed grade. The resources it provided have boosted research, resulting in new technologies such as a needlelike device that can be inserted into a tumor to test several drugs at once for effectiveness. But some things he thought essential and whose progress would be helped by federal support — like standardizing patient electronic records and increasing their portability between systems — have seen little improvement.*
*“Our ability to extract useful information from medical records is still woefully inadequate,” Demetri said. “The electronic medical records systems are better than chicken scratch on a piece of paper, but they still keep data in a very siloed way that is inefficient, unhelpful to research, and impossible to aggregate into a large-scale learning system.”*
Topics to be addressed in this resource include
- Mapping cancer rates
- Cancer anatomy
- Cancer clinical trials
- Molecular biology of cancers
- Patient-initiated research on cancer
These topics will be addressed in Jupyter notebooks, R markdown documents, and "shiny apps", to instruct in
both the subject matter of cancer data science, and the operation
of computational tools to solve problems in these areas.
To begin, please use the "Articles" link above.