Course content and learning goals

Metabolic engineering

  • Microbial cell factory development through metabolic engineering.
  • The use of computational modelling and omics data in metabolic engineering.

Computational modelling of metabolism

  • Learn the principles of constraint-based modelling, including flux balance analysis and model reconstruction.
  • Get hands-on experience in performing simulations with a genome-scale model using the RAVEN Toolbox.
  • Learn about the benefits of proteome- and enzyme-constrained modelling of metabolism.
  • Get hands-on experience in simulating enzyme-constrained models with GECKO Toolbox.

Bioreactor technologies

  • The various different modes by which microbial bioreactor cultivations can be done.
  • Suitability of the different cultivation modes for use with microbial cell factories.
  • Learn how to calculate rates from bioreactor cultivations, to use as input for constraint-based models.

Proteomics technologies

  • The various different approaches by which microbial proteomics can be performed.
  • The use of proteomics in the development and improvement of microbial cell factories.
  • Learn how to determine absolute quantitative protein levels, to use as input for enzyme-constrained models.

RNAseq data generation and analysis

  • Learn about the principles of RNAseq for differential gene expression analysis.
  • What to consider when designing an RNAseq experiment.
  • How to process the RNAseq data to ensure high quality analysis.
  • Get hands-on experience in converting raw RNAseq data into differential gene expression results.

Integrative data analysis

  • How various types of data can be combined to extract new hypotheses from your data.
  • Get hands-on experience in performing gene-set enrichment analysis with RNAseq data.