A hands-on workshop on data-driven DBTL cycles for metabolic engineering. This workshop walks participants through a complete iteration of the Design–Build–Test–Learn cycle using two complementary computational frameworks. In the first part, attendees will use Network Response Analysis (NRA) to interrogate an ensemble of kinetic models and identify rational enzyme intervention strategies that redirect metabolic flux toward desired phenotypes. In the second part, participants will apply a generative kinetic modeling framework to incorporate newly available experimental data from implemented designs back into the modeling pipeline — using a conditional variational autoencoder to enrich the kinetic ensemble with parameter sets that better reproduce the observed physiology. Together, the two parts demonstrate how model-guided design and generative learning can be tightly coupled to progressively sharpen predictive power across successive engineering cycles. Participants are expected to bring their own laptop to fully engage in the hands-on sessions.
Participants should have generated their gamspy free license following the instructions from the gamspy handbook here: https://drive.google.com/drive/folders/1fgDJomMlA_RCSWD1lKTcLmlr70SY12Xq?usp=share_link
Participants are advised to have the workshop folder downloaded and the environment running.
Workshop facilitators:
Stefanos Xenios (NTUA), Nikos Trokanas (NTUA), Antonis Kokossis (NTUA)
Organised by:
National Technical University of Athens (NTUA) as part of Horizon Europe project Bioindustry 4.0
Visit Website: https://ipsen.ntua.gr/
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