Sensitive data removal is critical to medical image sharing. Attend this two-day workshop to learn more about this topic and the role data science plays in de-identifying the data.

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.

NIH/NCI representatives will take part in this year’s Bio-IT World Conference & Expo, which showcases technologies and analytic approaches to accelerate science and drive the future of precision medicine. Check out their presentations if you want to learn more about “digital twins” and “FAIR” data!

In this webinar, Dr. Ma’ayan describes two new bioinformatics software tools he and his lab are developing. Learn how these data-integration tools can help in analyzing a variety of data types to better understand complex diseases, such as diabetes and cancer.

If you’re interested in how data plays a part in understanding sex differences in cancer, be sure to hear Jill Barnholtz-Sloan at this upcoming conference!

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

Interested in using quantitative imaging methods in preclinical and clinical trial settings? Attend this virtual meeting to network with others and to learn more.

Dr. Tolga Can of the Colorado School of Mines will discuss how he and his colleagues at Erson-Bensan Lab are using publicly available RNA-seq data sets and Cancer Genomics Cloud resources to screen for alternative polyadenylation events in cancer cells.

Want to learn more about data sharing and reuse practices that could be applied to your cancer research? This symposium will have a range of data science panels for you to choose from!

Hear from NCI’s Associate Director for Informatics and Data Science Program and learn about the intersection of data science and the future of cancer research.