Join the upcoming NCI Genomic Data Commons (GDC) monthly webinar to learn how to obtain access to controlled-access data.

Attend this workshop to help the National Institute of Standards and Technology’s (NIST’s) National Cybersecurity Center of Excellence (NCCoE) identify genomic data cybersecurity/privacy concerns and develop guidance to address these challenges. Genomic data are central to basic science research as well as disease (i.e., cancer) diagnosis and prediction.

Dr. Anant Madabhushi of Case Western University will discuss how his team is developing and using new artificial intelligence and machine learning methods to diagnose and predict therapy responses for a variety of cancers.

Join the January NCI Cancer Research Data Commons Cancer Genomics Cloud (CGC) webinar to learn how Dr. Michael Dean and Ms. Nicole Rossi used the CGC platform and tools to perform bioinformatic analysis on human papillomavirus sequencing data.

Attend this workshop to help data scientists and biomedical researchers explore the current capabilities, gaps, and opportunities for global data search across the data ecosystem.

Dr. Melissa Cline will explain how using federated analysis can help empower patients and healthcare providers to manage heritable cancer risk by analyzing rare genetic variants in BRCA1 and BRCA2 genes.

Learn how artificial intelligence is helping researchers model cancer risk and enhance cancer research.

During the SNO/NCI joint event, “Introduction to Career Pathways in Neuro-Oncology,” CBIIT’s Dr. Jill Barnholtz-Sloan will present “#DataMatters in neuro-oncology” to share the importance and impact of data science on central nervous system neoplasm research.

Join the December NCI Imaging and Informatics Community webinar to learn how Dr. Martin Yaffe’s team is developing imaging tools and a multi-platform approach to improve breast cancer detection and diagnosis.

In this webinar, Drs. Mancini and Gilmore will describe how different types of biomarkers (including those retrieved by a patient wearable) can be used to examine the effects of cancer and cancer treatment on trajectories related to aging. Examples include digital biomarkers related to gait and balance, as well as a biological biomarker reflecting epigenetic age.