GeneVa – Computing Metaoblic Valves on a Genetic Level

Bioprocesses are indispensable for the sustainable production of high value chemical compounds from renewable feedstock. In many processes, genetically engineered strains with a modified metabolism are used. Boosting the performance of such a production host can be essential to make a bioprocess profitable. Computational strain design provides methods to identify interventions in the microbial metabolism to increase its product yield or productivity.

The metabolic valve enumerator (MoVE), a tool that was developed in a former collaboration, computes strain designs for two-stage bioprocesses with increased yield and productivity, compared to classical processes. The project aims to enhance the existing algorithm to improve the quality and the applicability of the computed strain designs. This is done by taking genetic constraints into account. The student already implemented a technique for the integration of genetic constraints in another context. In the course of the project, the student will transfer this technique to the MoVE algorithm. The local researchers will help the student to get a deeper insight in the existing method “MoVE” and the underlying algorithm to plan and perform the integration.

Faculty Supervisor:

Radhakrishnan Mahadevan

Student:

Partner:

Max Planck Institute for Dynamics of Complex Technical Systems

Discipline:

Life Sciences

Sector:

Biotechnology; Information and Communications Technology; Sustainability & the Environment

University:

University of Toronto

Program: