Learn how to include a generalist repository in your data sharing plans and prepare for the new NIH Data Management and Sharing Policy, set to begin in January 2023.

Attend this upcoming NCI Containers and Workflows Interest Group webinar to learn how to create large-scale solutions for modern technologies using the Google Cloud Platform.

At the November NCI Imaging and Informatics Community Webinar, hear University of Maryland’s Dr. Eliot Siegel address both the gaps of applying AI into clinical practice and the possible solutions to advance adoption in the field of mammography.

Explore how data visualization, artificial intelligence, and virtual reality can help address challenges in mapping cell biology.

Attend this workshop to learn about EHR data and the issues/opportunities that come with it regarding childhood clinical care and cancer research. This workshop is organized by CBIIT Director Dr. Tony Kerlavage and CBIIT Office of Data Sharing Director Dr. Jaime Guidry Auvil.

Join researchers in discussion and collaboration around emerging cancer research, gaps, and opportunities.

European Molecular Biology Laboratory’s Dr. Alexandrov will review the profiling of the metabolism of individual cells by the emerging technology of single-cell metabolomics. This is the eighth of nine seminars in the SITC-NCI Computational Immuno-Oncology Webinar Series, designed for data scientists interested in the latest data science technologies and immunotherapy research.

An international symposium on RAS genes and proteins will be held on October 17–19, 2022. Of particular interest to data scientists will be a discussion on “ADMIRRAL—High Performance Computing Meets RAS/FAF Biology at the Membrane,” presented by Dr. Dwight Nissley.

Join the upcoming NCI Containers and Workflows Interest Group webinar to learn how Google can be used to advance NCI research, as exemplified through the NIH STRIDES Initiative.

Mark your calendar for the return of the NCI Imaging and Informatics Community Webinar. Speakers will give updates on the CRDC’s Imaging Data Commons and a new cloud-based platform for the dissemination of deep learning models.