Jennifer Kuehl

Jennifer Kuehl

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Jennifer Kuehl is a staff research associate that has worked for LBNL since 2002. She graduated from the University of Missouri- St.Louis with a BS in Biology. After graduation she drove to California for a vacation and stayed to start a life there. Her career at the lab started at the Joint Genome Institute in the Sanger sequencing production line as they were completing the human genome. She then transferred to the evolutionary genomics group at the JGI where the research was focused on using plasmids genomes for reconstructing the evolutionary history of everything from lettuce to worm lizards to stony corals to stalk eyed flies. In 2008, she started in the Arkin lab constructing a barcoded mutant library in the non-model sulfate reducing bacteria, Desulfovibrio alaskensis G20 for improving gene annotations. Currently she is working on pipeline to identify microbial interactions important for fitness in a given growth condition using high throughput enrichment culturing and 16s amplicon community sequencing. She feels fortunate to be able to work with and develop friendships with so many interesting Berkeley students from around the world.

XBD201808 00430 029 Fangchao Song

Fangchao Song

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Fangchao Song is a scientist at LLNL. He was a postdoctoral fellow in Arkin Lab at Lawrence Berkeley National Laboratory. Fangchao worked on droplet-based high throughput method to reveal bacterial interactions in complex microbial community and profile the microbial physiology in different nutrients and environments, under the project of Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA). Before joining the lab, Fangchao was a graduate student working on mathematical modeling of polymerization and biodegradable polymer manufacturing. In 2010, he started a new journey in the microbiology world during his Ph.D research on microbial biofilms and their antibiotic resistance. Since then, he is fascinated by the complexity and orderliness of microbiome, and enthusiastic about designing new method by combining experiments and modeling to better understand the function and dynamics of microbiome. Fangchao obtained his B.S. from Shandong University in 2003, M.S. from Zhejiang University in 2010, and Ph.D. from Syracuse University in 2016, all in Chemical Engineering.

Lauren Lui

Lauren Lui

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Lauren is interested in how we can use the latest sequencing technology to study environmental microbial communities, particularly nanopore sequencing.  She studied mathematical biology and bioinformatics at UC Davis, and received her PhD in Biomolecular Engineering and Bioinformatics from UC Santa Cruz. Ever since she started doing research, Lauren has sought to integrate quantitative and computational methods with experimental biology.  Currently, her projects include dissecting plant-microbe interactions with transposon mutant libraries, using synthetic microbial communities to understand the ecological and genetic factors of microbial interactions, and metagenomics of environmental microbes. Her ultimate goal is to be able to predict microbial interactions and community assembly from genome content and environmental measurements. In addition to her scientific work, Lauren is the co-secretary for the Women Scientists and Engineers Council at LBNL and loves doing photography, playing the ukulele, and illustrating with graphic arts.

Yolanda Yue Huang

Yolanda (Yue) Huang

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Yolanda is currently assistant professor at SUNY Buffalo. She was a postdoc in the Arkin lab and a Life Sciences Research Foundation (LSRF) fellow sponsored by Astellas Pharmaceuticals. She received her Bachelor’s from McGill University in Biochemistry. She completed her PhD in Chemical Biology with Emily Balskus at Harvard University where she characterized a new glycyl radical enzyme responsible for 4-hydroxyproline metabolism that is prevalent among gut anaerobes. In the Arkin lab, she worked to identify phage factors that influence bacterial physiology through multiple approaches – computational tools, data mining, and functional genomics.

Ruoshi Yuan

Ruoshi Yuan

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Ruoshi Yuan was a postdoc researcher in the Arkin lab at UC Berkeley/LBNL. He obtained his PhD in 2016 at Shanghai Jiao Tong University, China, supervised by Dr. Ping Ao. Then he did postdoctoral research at Harvard Medical School with Dr. Johan Paulsson. Ruoshi’s research interests include stochastic and nonlinear dynamics, mathematical modeling of biological phenomena, microbial interactions, complex diseases, and synthetic biology. Besides theory, he also works on high-throughput microfluidic experiments to obtain single cell time series data.

Astrid Terry

Astrid Terry

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Astrid Terry is the ENIGMA Project Manager. Her role is to monitor and enable progress of each project and investigator in the program and closely manage the budget. She coordinates and communicates updates, reports & publications to DOE. A major goal is identifying opportunities for collaboration, and increasing awareness of capabilities and resources available across the Science Focus Area.

Gwyneth Terry

Gwyneth Terry

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Gwyneth Terry is a senior administrator supporting Adam Arkin and his laboratory at Berkeley Lab and University of California, Berkeley. She has a BSc in geology from Cal State East Bay. She assists lab personnel with the UCB and LBL bureaucracy and helps moves science forward.

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Tuesday Simmons

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As of 2020, Tuesday is a Scientist at GALT.

SEAN CARIM

Sean Carim

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As of 2020, Sean is a Senior Scientist at 64x Bio.

Kelly Wetmore

Kelly Wetmore

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Kelly Wetmore is a graduate student in Adam Arkin’s lab at UC Berkeley with over 15 years of experience in microbial physiology and genetics before and during graduate school. She has been instrumental in developing a number of next-generation tools and protocols for microbial functional genomics. Kelly is supporting the CUBES team in applying these tools to optimize the core biomanufacturing microbes in physiologically more-or-less relevant conditions. She is also part of a large DOE environmental systems biology project in which she is developing a new technology to query high-throughput genetic interactions.