Cancer Data Science Pulse

The Cancer Data Science Pulse blog provides insights on trends, policies, initiatives, and innovation in the data science and cancer research communities from professionals dedicated to building a national cancer data ecosystem that enables new discoveries and reduces the burden of cancer.

Data and Artificial Intelligence (AI) are a match seemingly made in heaven. By joining data and AI, scientists are able to shift a lot of the burden associated with using data from human to machine. See why the data-AI relationship works so well for cancer research in this offbeat blog featuring two fictitious characters—Datum and his pal Aida.

At the start of the COVID-19 outbreak, NCI’s Frederick National Laboratory for Cancer Research, along with the Centers for Disease Control and Prevention and the National Institute of Allergy and Infectious Diseases, modified an existing tool used for managing NCI’s clinical trials to create a COVID-19 Seroprevalence Hub (SeroHub) to track COVID-19 seroprevalence across the United States. This blog looks at how SeroHub has evolved since the pandemic first began and shows how it could serve as a blueprint for monitoring future infectious disease outbreaks that threaten public health.

On April 20, Dr. Clemens Grassberger will present the next Data Science Seminar, “Computational and Mathematical Approaches to Modeling Immunotherapy-Radiotherapy Combinations.” Here, Dr. Grassberger describes how combining these two very different therapies—radiation and immunotherapy—may lead to stronger, more effective ways of treating cancer.

On April 6, Dr. Malachi Griffith will present the next Data Science Seminar, “Bioinformatics Approaches for Neoantigen Identification and Prioritization.” Here, Dr. Griffith tells how his tinkering with computers, bioinformatics, and genomics is helping him understand the complexities of this promising research area. If successful, neoantigen-based cancer therapies could prove to be the pinnacle of personalized medicine.

On March 23, Dr. Ben Raphael will present the next Data Science Seminar, “Quantifying tumor heterogeneity using single-cell and spatial sequencing.” In this blog, Dr. Raphael describes how he’s using this technology to dig deeper into the complexity of cancer.

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.

To celebrate the “International Day of Women and Girls in Science,” we asked CBIIT’s Associate Director for Informatics and Data Science, Dr. Jill Barnholtz-Sloan, to share her experience as a woman in data science. She tells about her journey to CBIIT and underscores the value of adding women’s perspectives to the data science field.

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.