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Advancing Watershed Understanding through Exascale Simulation and Machine Learning
ExaSheds is a new project led by Berkeley Lab PI Carl Steefel of the Earth and Environmental Science Area (EESA) and Oak Ridge National Lab co-PI Scott Painter. It represents the first systematic effort to leverage powerful machine learning and exascale computing, applied to ever-larger and more-complex data obtained from watershed field observations, to gain a predictive understanding of watershed behavior. The project is funded by DOE Biological and Environmental Research and will initially take advantage of datasets being collected at the East River, Colorado watershed site, which has been developed as part of Berkeley Lab’s DOE Watershed Function Science…
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Deepti Tanjore to Head ABPDU
Deepti Tanjore has been selected to be the next Program Head of the Advanced Biofuels and Bioproducts Process Development Unit (ABPDU). She has served as the Interim Program Head of the ABPDU since March 2019. She will also lead the Process Engineering and Analytics Department of the Biological Systems and Engineering (BSE) Division.
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Keasling Featured in NHK World, Japan’s Public TV Station
Jay Keasling, JBEI’s Chief Executive Officer, was featured in NHK World’s interview program “Direct Talk”. Keasling, a pioneer of synthetic biology, talks about the impact that this interdisciplinary technology can have in people’s lives as well as addresses its safety concerns. Direct Talk is a program that interviews leaders, visionaries and pioneers who shape the world and is broadcast to 300-million households in 160 countries in six different language subtitles. Watch the interview
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Exploring Human Origins in the Uncharted Territory of Our Chromosomes
A group of geneticists from Berkeley Lab, UC Davis, UC Santa Cruz, and UC Berkeley are unraveling new details about human evolution by studying the uniquely regulated portion of our chromosomes that surround the centromeres. These stretches of DNA – termed centromere-proximal regions (CPRs) – are largely composed of highly repetitive, mostly non-gene-coding sequences that […]
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More Investment Needed for Machine Learning for Bioengineering
In an opinion piece published July 19 in ACS Synthetic Biology, Hector Garcia Martin and Tijana Radivojevic of the Biosciences Area’s Biological Systems & Engineering Division collaborated with Pablo Carbonell of the Manchester Institute of Biotechnology’s SynBioChem Centre, to highlight the opportunities in a radical new approach to bioengineering that leverages the latest disruptive advances in machine learning.
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