News

Keep up with the latest news from the NCI Center for Biomedical Informatics and Information Technology (CBIIT) and the data science communities.

Tune in to hear how this small team of innovators is working to democratize data science education, break down barriers, and address health inequities in cancer.

Want to learn more about the noncoding regions of DNA that impact cancer and its resistance to treatment? A new NCI-funded computational tool called “MethNet” may help.

Looking for a new tool to help you better understand the genes that drive cancer? See how this NCI-funded tool called “HAPI” can help you spot structural changes linked to hijacked enhancers—bits of DNA that move from one location to another to boost overexpression of cancer-causing genes.

Apply for this NIH-supported opportunity to help advance the use of quantum computing to tackle real-world biomedical research problems, including cancer research.

Discover how you can use it to access and visualize genomic data, making it easier for you to analyze and interpret complex omics data.

Telomeres have confounded researchers for decades, making it difficult to understand their full impact on diseases like cancer. See how this new digital telomere measurement tool is helping researchers gain insight into these elusive structures.

Are you a tool developer who wants to apply your skills to support cancer research? Consider registering for this challenge where you’ll develop an analysis tool to integrate with NCI’s Genomic Data Commons.

Help define the data standards that will make data in the USCDI+ Cancer Registry interoperable with data collected for clinicals, public health, and research. Submit your feedback by Monday, September 23, 2024.

The funding opportunity aims to support Research Software Engineers in developing and disseminating biomedical, behavioral, or health-related software, tools, and algorithms.

NCI-funded researchers are blending mathematics with machine learning to refine cancer treatment. In the future, this kind of virtual tumor model could help to further personalize care for people with cancer.