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Article ID: 712798

Media Advisory: 2019 BioCompute Workshop on Next Generation Sequencing Data and Analysis

George Washington University

Together with the United States Food and Drug Administration and the BioCompute Partnership, the George Washington University is co-sponsoring a workshop, titled “BioCompute Objects: Tools for Communicating Next Generation Sequencing Data and Analysis.”

Released:
13-May-2019 4:30 PM EDT
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Article ID: 712674

Superfacility Framework Advances Photosynthesis Research

Lawrence Berkeley National Laboratory

For more than a decade, a team of international researchers led by Berkeley Lab bioscientists has been studying Photosystem II, a protein complex in green plants, algae, and cyanobacteria that plays a crucial role in photosynthesis. They’re now moving more quickly toward an understanding of this three-billion-year-old biological system, thanks to an integrated superfacility framework established between LCLS, ESnet, and NERSC.

Released:
9-May-2019 4:00 PM EDT
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Article ID: 712235

SDSC’s Sherlock Cloud Expands Hybrid Cloud Offerings

University of California San Diego

The Health Cyberinfrastructure (CI) Division of the San Diego Supercomputer Center (SDSC) at the University of California San Diego, has partnered with Microsoft Azure Cloud Services (Azure) to expand its portfolio of cloud services.

Released:
1-May-2019 3:05 PM EDT
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Article ID: 710932

Melissa Cragin Joins SDSC’s Research Data Services Group

University of California San Diego

The San Diego Supercomputer Center (SDSC) at the University of California San Diego announced today the appointment of Melissa Cragin as Chief Strategist for SDSC’s Research Data Services (RDS) group, effective immediately.

Released:
8-Apr-2019 2:05 PM EDT
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Article ID: 710920

SDSC’s Phylogenetics Science Gateway Awarded NSF/Internet2 Grant

University of California San Diego

The widely used CyberInfrastructure for Phylogenetic REsearch (CIPRES) science gateway, based at the San Diego Supercomputer Center (SDSC), has been awarded a one-year Internet2 grant funded by the NSF to give users AWS cloud access.

Released:
8-Apr-2019 12:05 PM EDT
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Article ID: 710912

Scientific computing in the cloud gets down to Earth

Los Alamos National Laboratory

In a groundbreaking effort, seismology researchers have conducted a continent-scale survey for seismic signatures of industrial activity in the Amazon Web Services commercial cloud (AWS), then rapidly downloaded the results without storing raw data or needing a local supercomputer.

Released:
8-Apr-2019 11:05 AM EDT
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Article ID: 710752

Berkeley Lab Team Uses Deep Learning to Help Veterans Administration Address Suicide Risks

Lawrence Berkeley National Laboratory

Researchers in Berkeley Lab's Computational Research Division are applying deep learning and analytics to electronic health record (EHR) data to help the Veterans Administration address a host of medical and psychological challenges affecting many of the nation’s 700,000 military veterans.

Released:
3-Apr-2019 6:05 PM EDT

Law and Public Policy

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Article ID: 710565

Supercomputers Aid Our Understanding of Complex Brain Waves

University of California San Diego

Leveraging the power of the Comet supercomputer at the San Diego Supercomputer Center (SDSC) at UC San Diego, campus researchers have demonstrated they can efficiently analyze more than 1,000 EEG 128-channel high-density data sets via the new Open EEGLAB Portal running on SDSC’s Neuroscience Gateway (NSG).

Released:
1-Apr-2019 2:05 PM EDT

Article ID: 710419

Ice Sheet Modeling Probes Antarctic Vulnerabilities

Lawrence Berkeley National Laboratory

The BISICLES ice sheet model uses high performance computing resources at the National Energy Research Scientific Computing Center (NERSC) to systematically examine where the Antarctic Ice Sheet is vulnerable and the resulting potential for large contributions to sea level rise.

Released:
28-Mar-2019 4:45 PM EDT
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Article ID: 710324

Modified deep-learning algorithms unveil features of shape-shifting proteins

Oak Ridge National Laboratory

To function properly, proteins must morph into specific 3D shapes through a biophysical phenomenon called protein folding. Researchers at ORNL are using various deep-learning techniques to study the intermediate protein stages between the initial unfolded state and the final folded state, which are notoriously difficult to characterize. These methods could also help identify factors that cause proteins to “misfold” into dysfunctional shapes, a phenomenon often attributed as a leading factor in the development of diseases including Alzheimer’s, cardiovascular disorders, and diabetes.

Released:
27-Mar-2019 2:05 PM EDT

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