News

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

Let NCI know what improvements you’d like to see when it comes to support for early career cancer researchers and trainees in data science.

Learn how you can employ NCI’s semantic infrastructure to expand the use of CDISC standards for Real-World Data analysis and the generation of Real-World Evidence.

NCI’s My Pediatric and Adult Rare Tumor Network (MyPART) program recently released a new long-term study, and an array of data resources, to help you in your research on rare cancers.

Explore a resource that lets you search for data challenges that address areas of unmet medical need!

Are you working with source codes, algorithms, workflows, and other software in your cancer research? NIH wants to hear from you! Respond today to help NIH develop new best-practice guidelines.

NIH wants to hear from you! Give your perspective on how to better use Real-World Data in biomedical and behavioral research.

Having trouble reproducing results from machine learning (ML) computational pathology studies? See how NCI’s Imaging Data Commons may be able to help, as evidenced by a new study.

Want to use multi-omics data to examine different genetic pathways underlying cancer, but you lack the necessary coding experience? Meet MOPAW, a new point-and-click interface that can help you make the most of your genetic data.

Do you use CCDI-managed data? Check out the CCDI Hub Explore Dashboard, a tool that allows you to discover CCDI-managed data and connect with participants and available samples and files.

In a recent study, NCI’s Dr. Haoyu Zhang describes CT-SLEB—a powerful and computationally scalable method for generating more precise polygenic risk scores across a range of ancestral groups (including Latino, African American, East Asian, and South Asian).