Cancer Data Science Pulse

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.

Much of our current understanding of the microbiome’s role in cancer can be attributed to advances in DNA sequencing and data science. Here, we look at a key NCI-supported bioinformatics tool called QIIME 2, which is helping us better understand the microbiome and its impact on disease.

On Wednesday, September 22, 2021, Yanjun Qi, Ph.D., from the University of Virginia, will present “AttentiveChrome: Deep Learning for Predicting Gene Expression from Histone Modifications,” in the kickoff of the Fall Data Science Seminar Series. This blog offers insight on Dr. Qi’s research and why this topic is important to her.

Technological advancements, such as machine learning and artificial intelligence, have made open data sharing more complex and put new pressure on existing laws that protect data privacy. This blog examines the privacy processes and policies that are helping address privacy concerns in today’s ever-changing “big data” landscape.

Data have been the driving force behind a number of important scientific discoveries. In this latest blog, Dr. Jerry Li describes how data helped power technological advances to unravel the human genome. What’s the next big advance? According to Dr. Li, the blending of data and artificial intelligence is the fastest moving area of research and has the potential to once again revolutionize scientific discovery.

Imagine a day when your healthcare is so personalized that there’s no guessing as to what medication will work best for you or whether you are at risk for a particular disease. This is a bold prediction recently addressed by genomic experts, Dr. Karen Miga and Dr. Evan Eichler. This blog examines how advances in technology are drawing us closer to a time when genomic information becomes a routine part of every patient’s healthcare.

“Count Me In” (CMI) is a unique project that gives patients an opportunity to share their cancer-related data directly with scientists. According to Corrie Painter, associate director of CMI, this is a largely untapped but vital part of data science. Here she describes the project and what it could mean for future research efforts.

The explosion of genetic information and direct access to large-scale genomic data not only opens up new areas for exploring today's most pressing research questions, it also serves as a reminder of the importance of collaboration at every stage of the study. NCI’s Dr. Daoud Meerzaman describes a new "circular" way of collaborating that keeps everyone in the loop when devising new genomics studies.