Skip to main content
ORNL researchers led by Michael Garvin, left, and David Kainer discovered genetic mutations called structural variants and linked them to autism spectrum disorders, demonstrating an approach that could be used to develop better diagnostics and drug therapies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.

ORNL’s Tomás Rush explores the secret lives of fungi and plants for insights into the interactions that determine plant health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.

ORNL scientists created a geodemographic cluster for the Atlanta metro area that identifies risk factors related to climate impacts. Credit: ORNL/U.S. Dept. of Energy

A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.

Earth Day

Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time. 

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.

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.

Researchers studying secondary metabolites in the fungus Aspergillus flavus, pictured, found unique mixes of metabolites corresponding to genetically distinct populations. The finding suggests local environmental conditions play a key role in secondary metabolite production, influencing the discovery of drugs and other useful compounds. Credit: Tomás Allen Rush/ORNL, U.S. Dept. of Energy.

Scientists at ORNL and the University of Wisconsin–Madison have discovered that genetically distinct populations within the same species of fungi can produce unique mixes of secondary metabolites, which are organic compounds with applications in

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.

Belinda Akpa applies her diverse expertise and high-performance computing to accelerate the drug discovery process and increase the chances of success when candidate molecules go to clinical trials. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Belinda Akpa is a chemical engineer with a talent for tackling big challenges and fostering inclusivity and diversity in the next generation of scientists.