News

The relaunched monthly CWIG webinar series will invite researchers from across the globe to discuss the latest advancements in cloud computing technologies, workflow, tools, and packages.

The latest terminology additions and changes have now been completed in NCI Thesaurus to support CDISC’s Study Data Tabulation Model and implementation guide, a standard model for submitting data from human clinical trials.

Data scientists, cancer biologists, and computational scientists are invited to submit abstracts to the Computational Approaches for Cancer Workshop (CAFCW21). Papers should focus on the application of computational approaches to cancer challenges, and those selected will be presented at the workshop. Abstract submissions are due by Monday, September 13.

Find terms from the NCI Thesaurus (NCIt) to include in your cancer research study, or learn what that term means for your data analysis, with a new browser, called EVS Explore. This tool builds on existing functionality available through the EVS Application Programming Interface and offers cancer researchers and data scientists a new, faster option for searching NCIt’s standardized cancer data.

Cancer clinicians, cancer biologists, and computational experts should apply to attend the four Combination Therapies for Cancer Treatment Micro Labs. Participants will work in teams and share ideas, expertise, data, code, results, and more, as well as explore opportunities for new data science and research collaborations. Each team will form, pitch, and refine plans for interdisciplinary strategies, priorities, projects, campaigns, and innovative approaches that advance scientific questions about cancer combinations therapies. One team may receive funding for their project.

Cancer researchers and data scientists can extract terms from the NCI Thesaurus (NCIt) and generate reports to show how those terms align with other standardized vocabularies with NCI’s new Report Exporter application.

NIH released this RFI to inform the development of consent language for data and biospecimen sharing.

NCI's Cancer Research Data Commons’ Imaging Data Commons has recently been featured in the official journal of the American Association for Cancer Research.

This RFI will inform the development of an NIH initiative on the use of Artificial Intelligence/Machine Learning to address health disparities and inequities and enhance diversity within the AI/ML workforce.

NCI's Cancer Research Data Commons’ Proteomic Data Commons has released accompanying proteomic data from the Clinical Proteomic Tumor Analysis Consortium Acute Myeloid Leukemia study.