Dr. Jeremy Goecks will share how cancer researchers are using the machine learning capabilities of the Galaxy project, one of the largest and most widely used open-source platforms for biomedical data science, to predict therapeutic responses and analyze tumor spatial biology.

Dr. Moseley is an Associate Director of the Institute for Biomedical Informatics at the University of Kentucky. His lab has a strong history of developing open-source software tools that enable access of public repository data including the Biological Magnetic Resonance Bank (BMRB), worldwide Protein Data Bank (wwPDB), and the Metabolomics Workbench (MWbench).

Join the February NCI Imaging and Informatics Community webinar to learn how Dr. Thomas Yankeelov’s laboratory is using quantitative imaging data to develop digital twins, a virtual representation of a cancer patient from real-world data, to predict risk and optimize therapy for cancer.

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.