Introductory reading in synthetic biology and our research

We are often asked by people outside of the synthetic biology field what they can read to get acquainted with it. Here is the list we usually give so they can get a taste of the field and our research:

Non-technical introduction

Introduction for non-scientists.

Short introduction (2-5 mins)

Here are a couple of videos that give a quick intro to synthetic biology (synbio):

And a very quick written introduction.

Medium introduction

A magazine article that explains the beginning of Amyris, one of the flagship companies in synbio:

"The Rise And Fall Of The Company That Was Going To Have Us All Using Biofuels"

Also, here are a couple of books we have found useful:

You can see further down how to interact with Berkeley Lab scientists.

Technical introduction

Introduction for scientists and people used to reading academic papers

Short introduction

See above in the non-technical section

Medium introduction

Here are some general reviews of synthetic biology:

"A brief history of synthetic biology" by Cameron et al.

"Synthetic and systems biology for microbial production of commodity chemicals" by Chubukov et al.

Long introduction

For a more detailed introduction, continue the previous section with some of our work in machine learning and flux modeling:

"A machine learning Automated Recommendation Tool for synthetic biology" by Radivojevic et al.

"Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism" by Zhang et al.

"A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data" by Costello et al.

"A Method to Constrain Genome-Scale Models with 13C Labeling Data" by Garcia Martin et al.

"13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids" by Ghosh et al.

and compare with more classical metabolic engineering work:

"Engineering dynamic pathway regulation using stress-response promoters" by Dahl et al.

"Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer" by Denby et al.

"Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering" by Alonso-Gutierrez et al.

Here are a few papers on automation and microfluidics, which we think will be critical in the future:

"Controlling an organic synthesis robot with machine learning to search for new reactivity" by Granda et al.

"Bioprocess automation on a Mini Pilot Plant enables fast quantitative microbial phenotyping" by Unthan et al.

"Automated flow-based/digital microfluidic platform integrated with onsite electroporation process for multiplex genetic engineering applications" by Iwai et al.

and some auxiliary tools we have developed to create the necessary infrastructure:

Arrowland for multiomics data visualization.

The Experiment Data Depot for experimental data collection and visualization.

ClusterCad for retrobiosynthesis.

For more of our papers you can have a look at the Research Interests section.

And some books we have found useful:

Interacting with scientists

Knowledge is power, but sometimes you want to talk to a person. Here are some community activities organized by Berkeley Lab:

Other Berkeley Lab community activities

You can find other ways to interact with Berkeley Lab scientists in this website.