ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
When reading the novel Jurassic Park as a teenager, Jerry Parks found the passages about gene sequencing and supercomputers fascinating, but never imagined he might someday pursue such futuristic-sounding science.
A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.
Scientists at ORNL have confirmed that bacteria-killing viruses called bacteriophages deploy a sneaky tactic when targeting their hosts: They use a standard genetic code when invading bacteria, then switch to an alternate code at later stages of
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.
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 had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
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.