Blog
Programming Microbes

Programming Microbes

At Zymergen we are building a data science ecosystem where machine learning algorithms help predict which genetic edits will produce strains with enhanced chemical production.

Zymergen Technology Team Values

Zymergen Technology Team Values

We’re proud of our team’s culture. As we grew, we found we wanted to write down the values that have created that culture. In this post we introduce the Zymergen Tech Team values, share the method we used to develop them, and provide additional commentary which we hope captures our thoughts and intentions behind each value.

AI in the Enterprise: Challenges and Opportunities (Part II: Challenges)

At Zymergen, we apply AI or machine learning techniques to many aspects of our high-throughput microbial genome assembly and testing systems and practices. Aaron Kimball, our CTO, offers his thoughts on what lessons we’ve learned as a result of this AI journey, and how these can be generalized to a broader business context.

AI in the Enterprise: Challenges and Opportunities (Part I: Opportunities)

At Zymergen, we apply AI or machine learning techniques to many aspects of our high-throughput microbial genome assembly and testing systems and practices. Aaron Kimball, our CTO, offers his thoughts on what lessons we’ve learned as a result of this AI journey, and how these can be generalized to a broader business context. In this two-part series, we will discuss first the opportunities and benefits brought to organizations by the use of AI.

Tips for Developing User-Facing Tools in Jupyter Notebooks

Tips for Developing User-Facing Tools in Jupyter Notebooks

At Zymergen, we use Jupyter notebooks to quickly create user interfaces for rapidly developed tools. In this post, we share code samples for developing IPython custom extensions, ipywidgets, and pandas dataframes displays to create user interfaces for Jupyter notebooks.

Software Engineering at Zymergen

Software Engineering at Zymergen

The Zymergen Technology organization is composed of Automation (the robots), Software (the code), Product Management (the plan), and IT (the gear). We invest in developing robust and flexible software to allow us to design new strains, track and guide high-throughput experimentation, collect and analyze process and performance data, and improve the overall accuracy and efficiency of all of our operations.