Learn how artificial intelligence is revolutionizing how we collect, study, and understand biomedical imaging data.

Are you having trouble finding gene sets to help in your research? Sign up for the January Data Science Seminar and learn about two new tools that can help make your task a little easier.

Learn more about Lancet, a somatic variant caller. This accurate, open-source tool leverages local assembly and joint analysis of tumor-normal, paired, high-throughput sequence data.

Find out how you can use NCI’s Proteomic Data Commons to advance your data-driven research.

Learn how researchers can use network models to understand the development and progression of diseases, such as cancer, and new ways to identify therapeutics.

During this webinar, New York University’s Dr. Itai Yanai will discuss the concept of cancer cell states present in a cancerous tumor prior to treatment, as well as those that accompany resistance to increasing drug doses.

Find out how longitudinal patient records impact cancer research, and how applying principles like transparency and reusability could improve this type of data!

Discover the results of the largest, real-world, federated learning study focusing on glioblastoma and leveraging data from thousands of patients across six continents. The speaker, Dr. Bakas, comes from the University of Pennsylvania’s Perelman School of Medicine.

Learn about a new cluster analysis model that provides insights into microbiome networks.

Learn more about open-source artificial intelligence and machine learning models available to you!