With an estimated 1.7 million new cases and 600,000 deaths during 2017 in the U.S. alone, cancer remains a critical healthcare challenge. Researchers used the Comet supercomputer at the San Diego Supercomputer Center (SDSC) to evaluate their new molecular docking tool which aims to improve immunotherapy outcomes by identifying more effective personalized treatments.
Lawrence Livermore National Laboratory scientists are contributing to the global fight against COVID-19 by combining artificial intelligence/machine learning, bioinformatics and supercomputing to help discover candidates for new antibodies and pharmaceutical drugs to combat the disease.
A professor in the Department of Biological Sciences at The University of Alabama in Huntsville (UAH) is part of an effort led by Oak Ridge National Laboratory (ORNL) in Tennessee that applies the power of supercomputers to screen compounds for effectiveness against the pandemic COVID-19 virus.
The U.S. Department of Energy (DOE) announced a plan to provide $60 million to establish multidisciplinary teams to develop new tools and techniques to harness supercomputers for scientific discovery.
The Department of Energy has a vital role to play in the national response to COVID-19. Researchers have already used tools at national laboratories to make major inroads to analyzing the virus and its spread.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have used Summit, the world’s most powerful and smartest supercomputer, to identify 77 small-molecule drug compounds that might warrant further study in the fight against the SARS-CoV-2 coronavirus, which is responsible for the COVID-19 disease outbreak.
Lawrence Livermore National Laboratory (LLNL), Hewlett Packard Enterprise (HPE) and Advanced Micro Devices, Inc. (AMD) today announced the selection of AMD as the node supplier for El Capitan, projected to be the world’s most powerful supercomputer when it is fully deployed in 2023.
Researchers at the University of Rhode Island (URI) used San Diego Supercomputer Center’s (SDSC) Comet supercomputer to show that high-performance computer modeling can accurately simulate tsunamis from volcanic events. Such models could lead to early-warning systems that could save lives and help minimize catastrophic property damage.
ORNL's Story Tips: Antidote chasing, traffic control and automatic modeling, for March 2020
Valentino Cooper of Oak Ridge National Laboratory uses theory, modeling and computation to improve fundamental understanding of advanced materials for next-generation energy and information technologies.
Lawrence Berkeley National Laboratory's decades of leadership in designing & enhancing energy-efficient data centers is being applied to NERSC supercomputing resources through a collaboration that's using operational data analytics to optimize cooling systems & save electricity.
Feature highlights PPPL accomplishments over the past 10 years.
To better leverage cancer data for research, scientists at ORNL are developing an artificial intelligence (AI)-based natural language processing tool to improve information extraction from textual pathology reports. In a first for cancer pathology reports, the team developed a multitask convolutional neural network (CNN)—a deep learning model that learns to perform tasks, such as identifying key words in a body of text, by processing language as a two-dimensional numerical dataset.
Researchers at the San Diego Supercomputer Center (SDSC) and the Wisconsin IceCube Particle Astrophysics Center (WIPAC) have conducted a second experimentt marshalled globally available-for-sale GPUs (graphics processing units), proving it is possible to elastically burst to very large scales of GPUs using the cloud, even in this pre-exascale era of computing.
The Protein Data Bank archive, which contains more than 160,000 3D structures for proteins, DNA, and RNA, this month released a new Coronavirus protease structure following the recent coronavirus outbreak, an ongoing viral epidemic primarily affecting mainland China that now threatens to spread to populations in other parts of the world.
Story Tips: Fusion squeeze, global image mapping, computing mental health and sodium batteries
Rice University engineers have created a deep learning computer system that taught itself to accurately predict extreme weather events, like heat waves, up to five days in advance using minimal information about current weather conditions.
Researchers at Oregon State University have been using the Comet supercomputer at the San Diego Supercomputer Center to test an algorithm that they believe will reduce errors in the widely used three-day forecasts for water temperature, salinity levels, sea heights, and currents off the coasts of Oregon and Washington.
An international team of researchers has discovered the hydrogen atoms in a metal hydride material are much more tightly spaced than had been predicted for decades—a feature that could possibly facilitate superconductivity at or near room temperature and pressure. The scientists conducted neutron scattering experiments at the Department of Energy’s Oak Ridge National Laboratory on samples of zirconium vanadium hydride.
Using supercomputer simulations and a large dataset of materials, scientists found a connection between distortions in the material’s atomic structure and the amount of energy required to separate a proton from the material.
RSS
Medicine keyboard_arrow_right
Sciencekeyboard_arrow_right
Life keyboard_arrow_right
Business keyboard_arrow_right
Journal News keyboard_arrow_right
By Location keyboard_arrow_right
Meetings, Grants, and Events keyboard_arrow_right