Several Biosciences Area personnel are among the 2018 Berkeley Lab Director’s Awards honorees. This annual program recognizes outstanding contributions by employees to all facets of Lab activities. A complete list of winners can be found here. Details on the awards ceremony will be posted in TABL.
More »
This summer the Biosciences Area has hosted student interns ranging from high school- through graduate school-level. They came to our laboratories through a number of programs dedicated to training the next generation of scientists. Some of our interns took time from their busy summer to share with us highlights of their experiences in the Biosciences Area.
The National Student Leadership Conference (NSLC) visited JBEI on July 17. NSLC is a nonprofit, nonpartisan, education organization which brings together high school students for fast-paced, high-level, interactive summer sessions. For a fifth year in a row JBEI and NSLC partnered to instruct students about the benefits and research behind biofuels and bioproducts.
Breakthrough discovery at the Joint BioEnergy Institute could greatly accelerate the pace of science
In the rapidly growing field of synthetic biology, in which organisms can be engineered to do things like decompose plastic and manufacture biofuels and medicines, production of custom DNA sequences is a fundamental tool for scientific discovery. Yet the process of DNA synthesis, which has remained virtually unchanged for more than 40 years, can be slow and unreliable.
Now in what could address a critical bottleneck in biology research, researchers at the Joint BioEnergy Institute (JBEI), announced they have pioneered a new way to synthesize DNA sequences through a creative use of enzymes that promises to be faster, cheaper, and more accurate. The discovery, led by JBEI graduate students Sebastian Palluk and Daniel Arlow, was published in Nature Biotechnology in a paper titled “De novo DNA Synthesis Using Polymerase-Nucleotide Conjugates.” Read the Berkeley Lab News Center feature story.
Héctor García Martin and Zak Costello, scientists affiliated with the DOE Agile BioFoundry, the Joint BioEnergy Institute (JBEI), and the Biological Systems and Engineering Division have developed a way to use machine learning to dramatically accelerate the design of microbes that produce biofuel.
Their computer algorithm starts with abundant data about the proteins and metabolites in a biofuel-producing microbial pathway, but no information about how the pathway actually works. It then uses data from previous experiments to learn how the pathway will behave. The scientists used the technique to automatically predict the amount of biofuel produced by pathways that have been added to E. coli bacterial cells. The research is published online in Nature Partner Journal Systems Biology and Applications. Read the Berkeley Lab News Center feature story.
Was this page useful?
