News

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.

NIH has issued a request for public comments on draft supplemental information to the NIH Policy for Data Management and Sharing. Responses will be accepted through June 27, 2022.

Genomic studies of childhood and rare cancers got a major boost, as a new optimized workflow for managing these data was recently reported in Nature Communications. And, thanks to funding by NCI’s Childhood Cancer Data Initiative, it’s easier and faster to share those data with the cancer research community.

In this JAMA Oncology Viewpoint opinion article, Dr. Jill Barnholtz-Sloan, NCI’s associate director for Informatics and Data Science, discusses NCI’s large-scale data sharing and access efforts. She also stresses that as we continue to generate cancer data, free and open scientific data should be treated as a public good.

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.

Two breast cancer imaging data collections have recently been released and made publicly available by The Cancer Imaging Archive. Together, these two collections comprise the first subgroup of publicly released imaging data from the I-SPY2 clinical trial.

Dr. Peng Jiang of NCI’s Center for Cancer Research Cancer Data Science Lab and his postdocs have developed an open-source computational tool called the tumor-resilient T cell (Tres) model. Tres analyzes gene activity in T cells to assess how those cells are likely to fare in an immunosuppressive environment.

Read about the latest NCI and Department of Energy workshops focused on advancing computational approaches for predictive radiation oncology. Next steps include addressing the unmet needs in radiation oncology and cancer research and aligning NCI-DOE project goals with the convergence of radiation therapy and advanced computing.

NCI’s Childhood Cancer Data Initiative has launched an inventory of childhood cancer data sets, repositories, and resources for investigators and data scientists alike.

Updates to NCIt, NCIm, and other terminologies/ontologies have been published and are now available. These resources, managed and maintained by NCI CBIIT’s Enterprise Vocabulary Service Team, promote harmonization and shared data standards. This latest update includes new data terms for the Pediatric Cancer Data Commons and the Integrated Canine Data Commons.