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

Are you looking for funding for your cancer informatics technology project? We highlight the most recent ITCR Funding Opportunity Announcements that may be right for you!

Learn more about NCI’s Request for Information and contribute to the conversation around cancer metabolomics data.

The latest update to the Childhood Cancer Data Catalog includes website improvements and the addition of the database of Genotypes and Phenotypes (dbGaP).

The latest update to the Childhood Cancer Data Catalog includes new and updated data, improved accessibility, as well as enhanced site search tools.

Using this knowledgebase, researchers may search for associations between molecular drug targets, diseases, and drugs specific for childhood cancers.

Cancer researchers can help NCI enhance cancer metabolomics research by applying for funding to develop innovative technologies and informatics tools. Learn about this Notice of Special Interest and how improving metabolomics technologies and their accessibility is advantageous for the advancement of cancer research.

Do you work with imaging data and tools? Share feedback on NCI’s Imaging Data Commons!

As the necessity for and availability of large data sets in cancer applications grows, so do the challenges when conducting research and clinical applications with computational solutions. Share your experience with how to address such challenges.

Data scientists, informaticists, and medical physicists are invited to develop the best, most generalizable models, algorithms, and approaches for breast density estimation using image-based distributed or federated learning.

The Frederick National Laboratory for Cancer Research’s Laboratory of Human Retrovirology and Immunoinformatics has updated its bioinformatics resource system known as DAVID. The system provides investigators with a set of functional annotation tools to better understand the biological meaning behind large lists of genes.