Cancer Data Science Pulse

Informatics Tools

In this blog, University of Maryland's Mrs. Aya Abdelsalam Ismail examines the use of Deep Learning in medical applications, especially as a means for following a disease or disorder over time. She’ll describe how a “wrong turn” in her research on forecasting Alzheimer’s Disease led her to question her model’s performance. Her findings are particularly relevant for Deep Learning models in the cancer field, which use images obtained from patients, often at different points in time.

Get to know David Kepplinger, Ph.D., who will present the next Data Science Seminar, “Robust Prediction of Stenosis from Protein Expression Data. ” In this Q&A, he describes who should attend the talk, how his topic relates to cancer, and why it’s important to delve into unexpected data values when conducting biostatistical analysis.

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.

The body’s microbiome has a profound effect on health and disease, including cancer. Read how the field of bioinformatics is helping define the microbiome’s composition and function, which could lead to new ways of treating cancer.

In recognizing the Power of Data and celebrating NCI’s 50th anniversary, we asked Dr. Ned Sharpless what data means to him and the field of cancer research. Read about his past experiences and where he thinks data will take cancer research in the future!

On May 24, CBIIT welcomed Dr. Jill Barnholtz-Sloan as the new associate director for Informatics and Data Science. In this latest Q&A blog, Dr. Barnholtz-Sloan tells a little about herself, including what brought her to CBIIT, what keeps her centered, and what makes her most proud.

Did you ever wonder what goes into making data ready for analysis by researchers around the world? Introducing “Datum.” This single speck of data was conceptualized to show how NCI’s Center for Biomedical Informatics and Information Technology supports cancer research by bringing data to life.

CBIIT’s May 19 Data Science Seminar Series speaker, Dr. Kristen Naegle, took the speed of computational biology, blended it with basic science know-how, and developed an algorithm that is proving to be remarkably effective in predicting kinase activity. Understanding kinases in oncology may help identify people who are more likely to respond (or not respond) to certain medications, further advancing precision medicine.

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.

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.