Collaboration on Yeast Modelling and Machine Learning
Forskningsprojekt, 2021
– 2023
Aims of the project:
* Expand the converage and accuracy of the yeast-GEM
* Develop and apply tools for Bayesian modellong to address uncertainty in genome-scale models
* Apply tools for macine learning based on big data and genome-scale models to better understand metabolism and predict novel metabolic engineering strategies
Deltagare
Verena Siewers (kontakt)
Chalmers, Life sciences, Systembiologi
Samarbetspartners
Danmarks Tekniske Universitet (DTU)
Lyngby, Denmark
Finansiering
Novo Nordisk Fonden
Projekt-id: CoopagreementChalmers/CFB
Finansierar Chalmers deltagande under 2021–2023
Relaterade styrkeområden och infrastruktur
Hälsa och teknik
Styrkeområden