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ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

Nesaraja split her effort between nuclear data evaluation and experimentation at ORNL’s now-closed Holifield Radioactive Ion Beam Facility. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Nuclear physicist Caroline Nesaraja of the Department of Energy’s Oak Ridge National Laboratory evaluates nuclear data vital to applied and basic sciences. 

The researchers embedded a programmable model into a D-Wave quantum computer chip. Credit: D-Wave

Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world.

ORNL’s Marcel Demarteau inspects experiments along Neutrino Alley at the Spallation Neutron Source, which makes neutrinos as a byproduct. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Marcel Demarteau is director of the Physics Division at the Department of Energy’s Oak Ridge National Laboratory. For topics from nuclear structure to astrophysics, he shapes ORNL’s physics research agenda.

Oak Ridge National Laboratory entrance sign

Rufus Ritchie came from Kentucky coal country, a region not known for producing physicists.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.