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

Are you having trouble prioritizing which genetic variants to study in your cancer research? There’s a new platform, called FORGEdb, that can help you pinpoint promising variants and target genes.

Interested in blending clinical and genetic data? Upgrades in cBioPortal can help you work with these very different data types to better understand cancer and how it progresses over time.

Do you conduct research on statistical and analytical methods, cancer survivorship, digital health, and/or data science tools and methods? Apply for an R01 grant from NCI’s Division of Cancer Control and Population Sciences by June 5 or October 5, 2024.

What if you could predict how a chemotherapy drug would work—in terms of sensitivity and side-effects—before you ever use it? NCI-funded researchers are using machine learning models to better understand a key mechanism underlying cancer, giving us new ways to predict responses to common chemotherapy drugs.

If you specialize in bioinformatics or computational biology, apply to study tumor heterogeneity, tumor evolution, and cutting-edge aspects of cancer genomics with NCI!

This Notice of Funding Opportunity will allow you to create and run a short course to educate early career researchers on using data sets available in NIH’s Common Fund.

NCI-funded researchers are using a machine learning approach to predict cancer outcomes based on epigenetic data, which take into account both environmental and genetic influences.

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.

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).

We’re seeking a qualified biomedical informatics specialist to join our CBIIT Team. Apply today for this unique opportunity to use data-driven approaches for advancing cancer research.