Synthetic Biology Concentration – UC Berkeley Department of Bioengineering

Concentration: Computational & Synthetic Biology

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Synthetic and computational biologists aim to design and build novel biological functions and systems by applying engineering design principles and computational tools to biology. This includes genome editing, modeling, and analysis of large sets of genomic data.

Sample Schedule

Real-World Applications

Drug discovery, green manufacturing, agriculture, customized materials, personalized medicine, bioethics.

Faculty who work in Computational & Synthetic Biology

J. Christopher Anderson

For more information, see: https://andersonlab.qb3.berkeley.edu/

Anderson Lab develops new applications and tools for the Synthetic Biology community. Our goal is to create a computationally-driven platform for the design of genetic organisms that minimizes the uncertainties and errors of such projects. Our platform is built around a computational method for encapsulating the function of biomolecules based on precise chemical models. Our platform aggregates data from various sources, then develops synthesis and verification tools to automatically design engineered organisms with new functions, demonstrated with bacterium that produces acetaminophen.

Adam Arkin

For more information, see: https://arkinlab.bio/

The Arkin Lab focus is how microbes transform, clean, and improve soils, soils that are currently degrading due to climate change, pollution, and poor water use. Near close-loops, low-energy, low-input biomanufacturing programs for food, pharmaceuticals, and building materials at “small village” scale, which are initially designed for a deep-space crewed Mars mission but have applications here on Earth for supporting sustainable agriculture. Another interest is to develop engineering approaches for microbiomes so we can control communities of microbes that drive the earth’s mineral cycles, support our plants and efficiency and stress responses, and impact the health and food-efficiency of a good many living creatures including ourselves.

Iain Clark

For more information, see: http://clarklab.berkeley.edu/

The Clark Lab develops microfluidic and molecular methods for the high throughput analysis of single cells. We use these techniques to study HIV latency in CD4 T cells and profile cellular interactions during central nervous system inflammation.

Irina Conboy

For more information, see: https://conboylab.berkeley.edu/

Our work has been focused on establishing new paradigms in multi-tissue stem cell aging, rejuvenation and regulation by conserved morphogenic signaling pathways. One of our goals is to define pharmacology for enhancing maintenance and repair of adult tissues in vivo. The spearheaded by us heterochronic parabiosis and blood apheresis studies have established that the process of aging is reversible through modulation of circulatory milieu. Our synthetic biology method of choice focuses on bio-orthogonal non-canonical amino acid tagging (BONCAT) and subsequent identification of age-imposed and disease-causal changes in mammalian proteomes in vivo. Our drug delivery reg medicine projects focus on CRISPR/Cas9 based therapeutics for more effective and safer gene editing.

John Dueber

For more information, see: https://dueberlab.berkeley.edu/

The Dueber Lab develops strategies for introducing designable, modular control over living cells. We are particularly interested in generating technologies for improving engineered metabolic pathway efficiency and directing flux. Our projects have applications in the development of biofuels, specialty chemicals, and environmentally friendly processes.

Leah Guthrie

For more information, see: https://www.theguthrielab.com/

The Guthrie lab investigates the principles that govern microbial metabolism and signaling in the context of kidney homeostasis and disease using mass spectrometry, chemoinformatics, and molecular biology approaches.

Teresa Head-Gordon

For more information, see: https://thglab.berkeley.edu/

The simultaneous revolutions in energy, molecular biology, nanotechnology and advanced scientific computing, is giving rise to new interdisciplinary research opportunities in computational science. The Head-Gordon lab embraces this large scope of science drivers through development of computational models and methodologies applied to molecular liquids, macromolecular assemblies, protein biophysics, and homogeneous, heterogeneous catalysis and biocatalysis. The development and application of complex chemistry models, accelerated sampling methods, coarse graining/multiscale techniques, and machine learning developed in her lab are widely disseminated through many community software codes that scale on high performance computing platforms.

Ian Holmes

For more information, see: https://biowiki.org/IanHolmes

The Holmes Lab brings techniques from machine learning, statistical linguistics, phylogenetics, and web development to bear on the interpretation and analysis of genomic data. Examples include the application of context-free grammars to understanding DNA and RNA structure; the use of phylogenetic methods in genome annotation, and to detect recombination breakpoints; the development of machine learning algorithms for bioinformatics models; the reconstruction of insertion, deletion and transposition events in genome evolutionary histories; statistical algorithms for metagenomics species distribution analysis; and dynamic-HTML web applications for collaborative genomic data analysis.

Patrick Hsu

For more information, see: http://patrickhsulab.org/

The Hsu Lab aims to understand and manipulate the genetic circuits that control brain and immune cell function to improve human health. We explore the rich biological diversity of nature to create new molecular technologies, perturb complex cellular processes at scale, and develop next-generation gene and cell therapies. To do this, our group draws from a palette of experimental and computational techniques including CRISPR-Cas systems, single cell genomics, engineered viruses, brain organoids, and pooled genetic screens. Current interests include 1) inventing novel approaches for editing the postmitotic genome, 2) developing engineered vehicles for therapeutic macromolecule delivery, and 3) leveraging library screens and brain organoids to interrogate human neuroscience at scale.

Jay Keasling

For more information, see: https://keaslinglab.lbl.gov/

Metabolic engineering, environmental biotechnology, and biochemical engineering.

Sanjay Kumar

For more information, see: https://kumarlab.berkeley.edu/

Our lab seeks to understand and engineer mechanical and other biophysical communication between cells and materials. In addition to investigating fundamental aspects of this problem with a variety of micro/nanoscale technologies, we are especially interested in discovering how this signaling regulates tumor and stem cell biology in the central nervous system. Recent directions have included: (1) Engineering new tissue-mimetic culture platforms for biophysical studies, molecular analysis, and screening; (2) Exploring mechanobiological signaling systems as targets for limiting the invasion of brain tumors and enhancing stem cell neurogenesis; and (3) Creating new biomaterials inspired by cellular structural networks.

Liana Lareau

For more information, see: http://www.lareaulab.org/

A single genome produces the huge diversity of cells and tissues needed to make a human by regulating gene expression to turn on and off the right genes at the right times. The final, post-transcriptional steps of gene expression — RNA processing and translation — are essential to the proper outcome. Our goal is to understand how these layers of regulation are encoded in gene sequences and how disruptions to this regulation can cause disease. Our research uses machine learning and other computational methods, coupled with high-throughput experiments, to understand how post-transcriptional regulation leads to robust and flexible control of gene expression.

Mohammad Reza Kaazempur Mofrad

For more information, see: https://biomechanics.berkeley.edu/

Molecular and Multiscale Biomechanics; Bioinformatics and Computational Biology; Statistical Machine Learning; Computational Precision Health; Microbiome; Personalized Medicine

Aaron Streets

For more information, see: https://streetslab.com/

The Streets lab is interested in applying lessons from mathematics, physics, and engineering, to invent tools that help us dissect and quantify complex biological systems. Our goal is to uncover laws that govern the interactions of molecules inside the cell and the interactions between cells in a tissue or organism, by making precision measurements on single cells. In pursuit of this goal, we exploit three core technologies; microfluidics, microscopy, and genomics.