In this one-week course, the foundations of machine learning will be laid out and commonly used methods for unsupervised (clustering, dimensionality reduction, visualization) and supervised (mainly classification) learning will be explained in detail. Methods will be illustrated using recent examples from the fields of systems biology and bioinformatics. Methods discussed in the morning lectures will be put into practice during the afternoon computer lab sessions.

In this course, we will cover genome analysis, variant analysis, and pangenomics. Core concepts, applications, and future trends will be discussed, with a focus on the algorithms and data structures underlying state-of-the-art methods. The course offers an engaging mix of lectures, paper discussions, hands-on tutorials, and a do-it-yourself project.

This course brings together contributions from different disciplines, i.e. bioprocess technology, applied physics, transport phenomena, molecular biology and biomedical sciences. They all address different elements on the coupling between several time and length scales in the simulation of different bioprocesses (e.g. bioreactor and bioprocess operation, microbial strain improvement, tissue and organ cultivation, plant design and integration). Computational methods will deepen the understanding of the connecting principles between different scales. The industrial relevance is underlined by the venue being the Biotech Campus Delft.

Constraint-based modeling is a powerful modeling methodology that is being used to model a diverse range of biological phenomena. These include both fundamental and applied questions relevant to biotechnology, microbiology and medicine. Central to constraint-based modeling is the use of genome-scale reconstructions that represent particular cellular functions as a biochemical reaction network. In this course, you will be introduced to …..

In this course the participants learn how to describe the dynamic behavior of biological systems, and how to use optimization techniques to solve a variety of problems in bioinformatics and systems biology. Concepts of modelling in terms of differential equations are introduced via a great variety of case studies taken from diverse practices. This course also provides you with the main ideas underlying optimization, and to get you acquainted with the optimization techniques that are nowadays available and widely used. Examples of optimization problems in life sciences will be presented and discussed.