Data-driven Engineering of Microbes for Sustainable Bioproduction
Abstract
Rational design of biosystems requires a profound knowledge about how changes in their genetic sequence affect their biological functions. Due to the complexity of biosystems, however, this relationship is still only vaguely understood. Our research aims at overcoming this limitation and enable straightforward engineering of microbes for sustainable bioproduction. We develop high-throughput methods enabling the recording of both sequence and function of genetic parts (regulatory elements, biosensors, enzymes etc.) at unprecedented scales. Further, we mine the resulting “big” sequence-function data by extracting valuable engineering guidelines and through building of predictive models for in silico design of sequences with tailored functions.
Rational design of biosystems requires a profound knowledge about how changes in their genetic sequence affect their biological functions. Due to the complexity of biosystems, however, this relationship is still only vaguely understood. Our research aims at overcoming this limitation and enable straightforward engineering of microbes for sustainable bioproduction. We develop high-throughput methods enabling the recording of both sequence and function of genetic parts (regulatory elements, biosensors, enzymes etc.) at unprecedented scales. Further, we mine the resulting “big” sequence-function data by extracting valuable engineering guidelines and through building of predictive models for in silico design of sequences with tailored functions.
Practical information
- General public
- Free
Contact
- Marta Ruiz Cumi: [email protected]