You have the power to use a team science-oriented field that is cutting-edge, valuable, and accessible. Invigorate your cancer research career with data science!
Have You Considered Using
Data Science for Your Cancer Research?
If you’re on this page, you’re wondering how you can leverage the power of
Whether you want to become a cancer data scientist or you’re just trying to figure out what you need to learn, we created this resource to answer:
Data Science to Cancer Research?
DATA SCIENCE DEFINITION
A team science-oriented field bringing together biology, computer science, statistics, mathematics, physics, artificial intelligence/machine learning, and complex modeling.
Cancer research generates a lot of data that is very difficult to analyze. However, this large-scale research is critical to making possible precision medicine efforts, or treatment options tailored to the personal genome of a patient. Cancer
Data Science Valuable to NCI?
NATIONAL CANCER PLAN
“I believe our role is to provide a usable data-and-infrastructure framework and to be a catalyst for action. I’m very optimistic about the future of cancer research, and I know data will be an integral part of that success.”
–Dr. Tony Kerlavage, Director of NCI Center for Biomedical Informatics and Information Technology (CBIIT)
As the nation’s leader in cancer research, NCI develops the technology, tools, and techniques that you and our own cancer researchers and data scientists can use. Identified as one of the eight goals outlined in the National Cancer Plan, maximizing data utility through
In your future projects, you might work with NCI
- You could share your research data or access other data sets in NCI’s cloud-based repository, the Cancer Research Data Commons.
- You may try out artificial intelligence (AI) and machine learning (ML) algorithms to investigate clinical targets through MoDaC.
- You might explore the pediatric molecular targets platform to study why some childhood, adolescent, and young adult cancer patients respond differently to treatments.
Data Science Valuable to You?
We’ve heard early career investigators ask:
- “Why do I need to learn this?”
- “Why learn this when I work with a data scientist?”
- “Can’t I just Google it or use ChatGPT?”
Late-career researchers told us they wished they had learned these basic skills when they started.
- expand your repertoire of research questions by blending different kinds of data (i.e., genomics, imaging, pathology, clinical studies) for integrative research.
- create algorithms that clean your data faster.
- improve your data visualizations for your publications.
- understand and evaluate the use and limitations of AI, ML, and large language models. If you don’t know how AI works, how can you have confidence in the results?
- be more marketable in your career.
Now that you’ve seen the possibility of cancer
How Can You Do Cancer
At NCI, our cancer researchers and data scientists often use a six-stage process that you can apply to your own research.
Ready to Get Started?
You see the value of