Cancer Data Science Pulse

Looking for ways to visualize your data? We asked data scientists to show us their favorite visualizations. Here, Dr. Alida Palmisano of NCI's Computational and Systems Biology Branch shares her ideas for visualizing complex single-cell RNA sequencing data.

Watch our time capsule video to learn about the current status of the field and new technologies that are sure to be important as we embark on the next era of cancer data research.

Discover how NIH is working to make generalist repositories (GRs) part of the data sharing ecosystem. The goal is to minimize data sharing barriers while still taking advantage of GR convenience and usability.

We asked 8 of our data scientists across the National Cancer Institute to share their advice and career journeys to help you answer the question—what should I know to start my career in cancer data science?

Meet the people who are breaking new ground in the data science field, whether it’s a new tool, a new model, or a completely new way of using data. Here, we’re featuring Svitlana Volkova, Ph.D., chief scientist at Pacific Northwest National Laboratory. She’ll describe how she’s using “foundation models” to give scientists and analysts a new tool for unleashing the power of artificial intelligence (AI).

CBIIT’s NIH Data and Technology Advancement (DATA) Scholar, Dr. Jay G. Ronquillo, offers a bird’s-eye view of cloud computing, including tips for managing costs, access, and training to help advance precision medicine and cancer research.

In this blog, Dr. Elana J. Fertig describes how she is using artificial intelligence, blended with spatial and single cell technologies, to better understand how cancer will respond to treatment. Predicting the changes that occur in the tumor during treatment may someday enable us to select therapies in advance, essentially stopping the disease in its tracks before it reaches the next stage in its evolution.

Staying afloat in today’s torrent of data sets, tools, and applications calls for both a deep knowledge of cancer, as well as the know-how to apply highly specialized technological solutions. A new resource from NCI’s Informatics Technology for Cancer Research program gives researchers, with varying skills and experience, the training they need to manage technology-driven approaches to cancer research and care.

Converting the many petabytes of cancer data available on the cloud from information to answers is a complex task. In this blog, Deena Bleich shares how the ISB Cancer Gateway in the Cloud (ISB-CGC), an NCI Cloud Resource, hosts large quantities of cancer data in easily accessible Google BigQuery tables, expediting the process.

This blog offers a primer on semantics, a topic that has broad implications for the biomedical informatics and data science fields. Here, Gilberto Fragoso, Ph.D., describes the structures that serve as a foundation for data science semantics. Those systems help improve data interoperability, allowing researchers to query, retrieve, and combine very different data sets for more extensive analysis.