Data Science
Revolutionizing Cancer Research
We’re making new discoveries faster using the vast and growing amounts of molecular and health data available to our scientists — thanks to your support.
What Is Data Science?
Data science is the practice of transforming large amounts of complex data into meaningful information. Data scientists are part mathematician, part computer scientist and part trend-spotter. These software engineers, statisticians and programmers use computational tools to solve biological problems.
Philanthropy has been instrumental in helping Fred Hutch’s data scientists use existing tools and invent new ones to find patterns that expose cancer’s secrets and extract lessons that improve care for patients. Using machine learning, deep neural networks, natural language processing and cloud computing, we have the power to find more meaning in data, at much deeper levels, than previously imagined.
Join us in fueling discoveries for the patients of today and tomorrow.
Data Science Is Already Breaking New Ground
Using AI to Identify New Therapies
Fred Hutch researchers have used machine learning, deep neural networks and other artificial intelligence tools to screen, identify and validate a handful of compounds, some Food and Drug Administration–approved, that may provide benefit to patients with COVID-19 or cancer.
Unearthing the History of Coronaviruses
Our researchers found that some coronaviruses’ ability to jump from one species to the next could be a more widespread possibility than previously thought. Instead of being a late evolutionary development, the ability to bind ACE2, the point of entry for SARV-CoV2, is an ancient property of bat SARS-related coronaviruses.
Preventing, Detecting and Treating Cancer through the Microbiome
Several teams are combining data science and extraordinary laboratory tools to find surprising connections between cancer, our immune system and the communities of microbes that inhabit us. Their work may have implications for patients with many different cancers, as well as those who have received a bone marrow transplant.
Separating Fact from Fiction in Breast Cancer Overdiagnosis
With a deep dive into data from the Breast Cancer Surveillance Consortium, Fred Hutch researchers projected that just 15% of people who have breast cancer detected through screening will be overdiagnosed — potentially dispelling some fears that mammograms caused more harm than good.
Featured Researchers
Dr. Jeffrey Leek
Dr. Leek, who holds the J. Orin Edson Foundation Endowed Chair, leads efforts to shape and implement Fred Hutch's integrated data science enterprise and fosters partnerships within the Seattle area's data science and technology ecosystem.
Dr. Robert Bradley
Dr. Bradley, who holds the McIlwain Family Endowed Chair in Data Science, is a computational biologist and biophysicist who works at the intersection of several different disciplines, including cancer biology, cancer-immune interactions and RNA processing.
Dr. Trevor Bedford
Dr. Bedford uses powerful computers and complex statistical methods to study the rapid spread and evolution of viruses, including those that cause COVID-19, influenza, Ebola and Zika.
Dr. Ruth Etzioni
Dr. Ruth Etzioni, who holds the Rosalie and Harold Rae Brown Endowed Chair, is a biostatistician who focuses on cancer screening and early detection in the areas of prostate and breast cancer, where she uses data to do everything from evaluate tests to measure the impact of screenings.