Given a small library of mutants (at a few sites) of a WT with annotations, propose new mutants to synthesize and investigate.Let us distinguish a few use cases, which differ in the available data and in the task of the model: Unlike rational design from a well-understood chemical or quantum-mechanical description, design by statistical models will only succeed if the data together with the inductive bias of the models give enough information. However, if the design of new variants uses sufficiently good predictive models, it becomes more likely to hit an interesting variant, thus possibly compensating for the higher cost of the individual synthesis. How useful are statistical models or machine learning tools as a a complement to directed evolution? Each variant in a random library that is screened for a property of interest (enzymatic activity, stereoselectivity, stability) comes cheap compared to the synthesis of specific variants. 1h hands-on experiments using the tools.tea/coffee break for contacting and experience exchange 1h interactive presentation of selected computational tools.Biochemistry Seminarroom D213, 2nd floor. Sub-Workshop: Statistical models/machine learning as a complement to directed evolution in the search for new enzymes Stefan Born, (Mark Doerr) Stefan Born Maak Doerr workshop will be divided into two parts: Part I. Locaction: Institute for Biochemistry, Felix-Hausdorff 4, 2nd floor, Seminarroom D213 (for the ones, who are already early in Greifswald) The workshop is free and open to all, but due to space limitations (10-15 people) we kindly ask to register for the workshop: simply write an e-mail to : 9:00-15:00h Automation in enzymatic research: Software for the high-throughput lab and computational tools (machine learning)

Subworkshop