A team of researchers led by Cheryl Kerfeld, faculty affiliate in the Environmental Genomics & Systems Biology (EGSB) Division, have developed a new method to manipulate miniature factories found in bacteria that could someday lead to new medical, industrial, or energy applications. The factories, called bacterial microcompartments – or BMCs – are found in bacteria all over the world.
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Two scientists from the Biosciences Area, Sung-Hou Kim and Susannah Tringe, have been named Fellows of the American Association for the Advancement of Science (AAAS). They join fellow Lab scientists Allen Goldsten, faculty scientist in the Energy Technologies Area, and Kathy Yelick, associate laboratory director of Computing Sciences, in receiving the distinction of Fellow this year for “their scientifically or socially distinguished efforts to advance science or its applications.”
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On November 15, 2018, at the International Conference for High Performance Computing, Networking, Storage and Analysis (SC18) Conference, teams led by Lawrence Berkeley National Laboratory (Berkeley Lab) and Oak Ridge National Laboratory (ORNL), respectively, shared the 2018 ACM Gordon Bell Prize.
Congratulations to JGI’s Chief Informatics Officer Kjiersten Fagnan, who was part of the ORNL-led, seven-member team. The 12-member Berkeley Lab team was recognized for training a deep neural network to identify extreme weather patterns from high-resolution climate simulations using high-performance computers.
Read the full story on the JGI website.
Berkeley Lab researchers, in collaboration with scientists from SLAC National Accelerator Laboratory and the Max Planck Institute, have demonstrated that fluctuation X-ray scattering is capable of capturing the behavior of biological systems in unprecedented detail. Although this technique was first proposed more than four decades ago, its implementation was hindered by the lack of sufficiently powerful X-ray sources and associated detector technology, sample delivery methods, and the means to analyze the data. The team developed a novel mathematical and data analyses framework that was applied to data obtained from DOE’s Linac Coherent Light Source (LCLS) at SLAC. This breakthrough was recently reported in the Proceedings of the National Academy of Sciences (PNAS).
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Researchers from Berkeley Lab and the Allen Institute for Brain Science will receive $2 million from the National Institutes of Health (NIH) to develop a next-generation data format and software ecosystem for the Neurodata Without Borders: Neurophysiology (NWB:N) project. With funding from the Kavli Foundation, Berkeley Lab scientists Oliver Ruebel and Andrew Tritt in the Computational Research Division and Kristofer Bouchard in the Biological Systems and Engineering Division led the development of the beta version of NWB:N 2.0, and will continue to advance the development of NWB:N as part of the NIH BRAIN Initiative. Berkeley Lab’s leadership in the NWB:N development would have not been possible without the Laboratory Directed Research and Development (LDRD) project BRAINformat: A Data Standardization Framework for Neuroscience Data. Berkeley Lab also hosted a user engagement hackathon earlier this year, bringing together users to help them adopt NWB:N.
Read more from Computing Sciences.
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