News

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

NCI-funded researchers are using machine learning to help identify an early-warning screening approach for colorectal cancer.

Want to identify existing gene mutations more accurately and discover new signatures more efficiently? There’s a new NCI-funded tool, the Mutational Signature Calculator, that can help improve your standard workflow.

CAFCW24 is an opportunity to collaborate with experts in data science, computational biology, artificial intelligence (AI), computer science, and other disciplines to drive cancer research and innovation.

Dr. Jill Barnholtz-Sloan is CBIIT’s new acting director following Dr. Tony Kerlavage’s retirement last week. In addition to this role, Dr. Barnholtz-Sloan maintains her responsibility as associate director for the Informatics and Data Science Program and senior investigator in the Division of Cancer Epidemiology and Genetics, Trans-Divisional Research Program.

Are you researching immunotherapies and having trouble predicting which epitope will deliver the biggest punch? Try this new model for predicting immunogenicity, which is reportedly outperforming current models.

See the digital health technologies informed consent resource that your Request for Information responses helped create!

In the “Mitelman Gene Fusions in TCGA” notebook, ISB Cancer Gateway in the Cloud (an NCI Cloud Resource) identified the most common gene fusions in prostate adenocarcinoma, demonstrating machine learning in Google BigQuery.

NCI’s Childhood Cancer Data Initiative (CCDI) invites proposals from laboratories with the capability to perform multi-omics research-grade molecular characterization for submission to the CCDI Data Ecosystem. Apply by June 14, 2024, at 3:00 p.m. ET.

Are you curious about NCI’s current research? Use NCI’s newly updated Index of Studies to learn about the projects underway, including focus areas and cancer types.

Are you developing digital twin technology and looking for possible funding? The National Science Foundation, NIH, and the U.S. Food and Drug Administration will fund 6–10 new digital twin projects.