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.

Dr. Charles Wang offers a sneak peek at his upcoming Data Science Seminar presentation, scheduled for April 7. His recent study provides guidance for choosing an appropriate scRNA-seq platform and software tool for a scRNA-seq study. Using these guidelines, scientists can select the workflow that will yield the most meaningful results.

What do winter storms, airplanes, and cancer research have in common? In this blog, experts on meteorology, aerospace engineering, and radiation oncology explore what we can learn from these very different fields to further advance how we target and apply radiation to more effectively treat cancerous tumors.

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.

Artificial Intelligence offers boundless possibilities, especially in the healthcare field. In a recent CBIIT Data Science Seminar, Dr. James Zou showed how Computer Vision (CV) is helping create a new data-driven “language of morphology” that allows researchers to be more precise in interpreting histological images. Just as computers help propel self-driving cars along busy roadways, CV offers a faster, less-subjective method for assessing disease.

Our newest “Spotlight” features Jennifer Kwok, program manager in CBIIT’s Infrastructure and Information Technology Operations Branch. Much of her work centers on developing IT solutions for NCI staff and organizations to streamline and optimize their business functions and processes.

“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.

On October 20th, NCI launched the Imaging Data Commons (IDC), the latest data repository to be offered within the Cancer Research Data Commons (CRDC) infrastructure. Through the IDC, both researchers and clinicians will have access to a wide range of cancer-related images, including radiology and pathology imaging data, as well as their accompanying metadata.

NCI offers a broad range of fellowships, enabling us to tap some of the brightest minds in science and technology to further advance scientific discovery. Here, Joseph Flores-Toro, Ph.D., a fellow in the Office of Data Sharing (ODS), describes the path he took in becoming a fellow for CBIIT.

Dr. Tony Kerlavage, director of NCI’s Center for Biomedical Informatics and Information Technology (CBIIT), sat down to discuss one key component of racial inequality, the issue of health disparities, as it relates to Big Data. As noted by Dr. Kerlavage, representing our diverse U.S. population in research and in the workforce are key, but we also need better data.

Naturally occurring cancers in dogs share similarities with cancer that occurs in humans. The Integrated Canine Data Commons (ICDC), a cloud-based repository of canine cancer data, includes a variety of molecular, clinical, pharmacological, and medical imaging information from pet dogs. Such comparative oncology findings offer researchers greater insight into how best to diagnose, treat, and prevent cancer—in both people and pets.