We believe that biological systems have the potential to perform much better than current electronic computers in solving problems, especially biological problems. Our research aims to learn how to design a "biocomputer" by making it.

Artificial cells

The ultimate goal to program biology is to create new species. Our research on designing new life forms aligns our understanding with the fundamentals of biology. At the current stage, we focus on filling the gaps between kingdoms, such as recreating eukaryotic structures in prokaryotes, and transiting unicellular organisms into multicellular ones.

Highlights -- the first eukaryotic-like organelle built in E. coli, first reported in iGEM 2017 and then published in Cell 2022, featured by Chemistry World and Nature Biotechnology.

Lab in a cell

Our research on biocomputing has led to systems that use biological components to perceive, decide, and act.

In memory of Dan Tawfik, these biocomputing "programs" can be both miniaturized and parallelized into cell or alike compartments, and turning them into microscale laboratories that operate R&D and production tasks automatically.

Accordingly, these "labs" in "cells" can perform on a massive scale to generate biologically relevant data, much more efficiently than humans, robots, and electronic computers.

AI-automated research

Our capability to acquire large amounts of experimental data enables training of AI systems that generate, predict and redesign biological systems with high relevancy and accuracy.

Pretrained language models further interfaces scientists and the systems we design, to streamline or even automate the entire R&D process.

Highlights -- Machine learning guided design and evolution of antimicrobial peptides (iGEM Paris Bettencourt 2018)