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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. 

Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals. Credit: ORNL, U.S. Dept. of Energy

Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.

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.

ORNL’s biosensor system reveals CRISPR activity in poplar plants, which glow bright green under ultraviolet light, compared to normal plants, which appear red. Credit: Guoliang Yuan/ORNL, U.S. Dept. of Energy

Detecting the activity of CRISPR gene editing tools in organisms with the naked eye and an ultraviolet flashlight is now possible using technology developed at ORNL. 

ORNL’s Larry York studies how plant root traits contribute to crop productivity. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Biologist Larry York’s fascination with plant roots has spurred his research across four continents and inspired him to create accessible tools that enable others to explore the underground world.

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.

Carrie Eckert

Carrie Eckert applies her skills as a synthetic biologist at ORNL to turn microorganisms into tiny factories that produce a variety of valuable fuels, chemicals and materials for the growing bioeconomy.

The ectomycorrhizal fungus Laccaria bicolor, shown in green, envelops the roots of a transgenic switchgrass plant. Switchgrass is not known to interact with this type of fungi naturally; the added PtLecRLK1 gene tells the plant to engage the fungus. Credit: ORNL, U.S. Dept. of Energy

An ORNL team has successfully introduced a poplar gene into switchgrass, an important biofuel source, that allows switchgrass to interact with a beneficial fungus, ultimately boosting the grass’ growth and viability in changing environments.

Fine roots from a larch tree peek out from a pile of peat excavated from an experimental warming plot in the SPRUCE experiment in Northern Minnesota. Credit: Colleen Iversen/ORNL, U.S. Dept. of Energy

New data hosted by Oak Ridge National Laboratory is helping scientists around the world understand the secret lives of plant roots as well as their impact on the global carbon cycle and climate change.

Scientists at Oak Ridge National Laboratory added new plant data to a computer model that simulates Arctic ecosystems, enabling it to better predict how vegetation in rapidly warming northern environments may respond to climate change.

Scientists at Oak Ridge National Laboratory added new plant data to a computer model that simulates Arctic ecosystems, enabling it to better predict how vegetation in rapidly warming northern environments may respond to climate change.