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A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

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.

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers. Credit: ORNL, U.S. Dept. of Energy

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.

Peter Thornton, right, works with Robertsville Middle School students to assemble the RamSat. Credit: Ian Goethert/ORNL, U.S. Dept. of Energy

RamSat’s mission is to take pictures of the forests around Gatlinburg, which were destroyed by wildfire in 2016. The mission is wholly designed and carried out by students, teachers and mentors, with support from numerous organizations, including Oak Ridge National Laboratory.

ATOM logo

The Accelerating Therapeutics for Opportunities in Medicine , or ATOM, consortium today announced the U.S. Department of Energy’s Oak Ridge, Argonne and Brookhaven national laboratories are joining the consortium to further develop ATOM’s artificial intelligence, or AI-driven, drug discovery platform.

Verónica Melesse Vergara speaks with third and fourth graders at East Side Intermediate School in Brownsville. Credit: ORNL, U.S. Dept. of Energy

Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.

Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

Paul Kent, shown above posing with Summit in April 2018, received the 2020 ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy

The annual Director's Awards recognized four individuals and teams including awards for leadership in quantum simulation development and application on high-performance computing platforms, and revolutionary advancements in the area of microbial

ORNL assisted in investigating proteins called porins, one shown in red, which are found in the protective outer membrane of certain disease-causing bacteria and tether the membrane to the cell wall. Credit: Hyea (Sunny) Hwang/Georgia Tech and ORNL, U.S. Dept. of Energy

Scientists from Oak Ridge National Laboratory used high-performance computing to create protein models that helped reveal how the outer membrane is tethered to the cell membrane in certain bacteria.

Analyses of lung fluid cells from COVID-19 patients conducted on the nation’s fastest supercomputer point to gene expression patterns that may explain the runaway symptoms produced by the body’s response to SARS-CoV-2. Credit: Jason B. Smith/ORNL, U.S. Dept. of Energy

A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.