Synthetic Biology Concentration – UC Berkeley Department of Bioengineering

Concentration: Computational & Synthetic Biology

decorative image of data on computer screen

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.

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.

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.berkeley.edu/

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.

News About: Computational & Synthetic Biology

Highly Cited Researchers 2020 Clarivate banner image

Four BioE Faculty Named 2025 Highly Cited Researchers

Professors Paul Adams, Adam Arkin, Patrick Hsu, and Jay Keasling have been recognized in the “2025 Highly Cited Researchers” list, meaning their work ranks in the top 1% of citations for their field and publication year in Clarivate’s Web of Science citation index

Taner Sen and Colleagues Sequence Complex Oat Pangenome

Adjunct Professor Taner Sen and his colleagues at the USDA and beyond have assembled and annotated the genomes of 33 wild and domesticated oat lines, along with an atlas of gene expression across in 23 of these lines, which will enable future efforts to even more hardy and productive strains of the popular grain.

head and shoulders photo of Keasling in lab examining a flask of fluid. photo by JBEI

Keasling Named 2025 DOE/NAI Innovator of the Year

The Department of Energy and the National Academy of Inventors have honored Professor Jay Keasling with their 2025 Innovator of the Year Award, which goes to one DOE employee who has translated research into tangible impacts that have benefited society at large. Keasling is a pioneer in synthetic biology who leads a groundbreaking research program focused on engineering microorganisms to produce advanced biofuels and chemicals.

microscope image of osteoyeast cells. The outline of the vacuole is red, the calcium inside the vacuole is green. Image by Berkeley Lab.

New Process Uses Microbes to Create Valuable Materials from Urine

A team led by BioE alumnus Yasuo Yoshikuni genetically modified yeast to create hydroxyapatite, a strong and lightweight material, from the elements present in urine. With lower production costs the material may now be practical for use in wastewater treatment, fertilizer manufacturing, building materials and plastic replacement.