Synthetic biology is fundamental to the technology of the 21st century. There are many challenges before we can realize rational design of biological systems. At the same time, biology allows for some additional engineering techniques, such as directed evolution, which have yet to be fully exploited.
We are interested in developing bioinformatics tools and infrastructure for synthetic biology including AI, ontologies, information theory, statistical machine learning, deep learning, and web technology. Applications range broadly across synthetic biology including e.g. AAV capsid engineering for drug delivery, or enzyme engineering for biotechnology.
In more blue-sky research, we are also interested in computational simulations of folding and replication kinetics of synthetic and abiogenetic nucleic acid sequences, with a goal to understanding DNA and RNA nanotechnology (including e.g. novel riboswitch and ribozyme complexes, or codes for DNA data storage) as well as computational simulation of the origin of life.