Module 2 [1 ECTS] - Advanced AI Techniques in Biological Systems

Start date: Week 36 (3rd September 2024)

Speaker 1: Patrick Bryant (Ass. Prof. at SU & DDLS Fellow; Tuesday 3rd September 8:00-9:00 CEST)

Patrick Bryant’s research seeks to answer questions about the evolution of proteins and how this information can be used to create a new range of AI tools. Google Scholar

Title: Protein structure prediction and design

The foundation of protein design is accurate structure prediction which depends on coevolutionary patterns found in multiple sequence alignments (MSAs). Coevolution constrains the protein structure just enough for it to become predictable given a suitable MSA. However, designing new proteins poses a challenge in the absence of coevolutionary data. Therefore, protein design methodologies must incorporate learned associations between amino acid sequences and protein structures, encapsulating the rules governing the known protein space. In this lecture, you will learn more about how to design new proteins and in the practical session you will design your own peptide binder using the latest structure prediction technology.

Speaker 2: Johan Bengtsson-Palme (DDLS Fellow at Chalmers University of Technology; Tuesday 3rd September 9:00-10:00 CEST)

Johan Bengtsson-Palme holds a PhD in Medicine from the University of Gothenburg, where he focused on the role of the environment in antibiotic resistance development. He completed a postdoc on interactions in microbial communities with Prof. Jo Handelsman at the University of Wisconsin-Madison (USA). As of May 2022, he leads a research group working on data-driven microbiology. Read more on the group website at

Title: Large-scale predictions of antibiotic resistance in microbial communities

This lecture will focus on how we can predict antibiotic resistance and virulence in bacterial communities through large-scale experiments, metagenomics and bioinformatics. We will discuss methods to identify antibiotic resistance genes, investigate their potential for transfer to pathogens, and predict where bacteria carrying resistance are found. We will integrate methods under development in the EMBARK and SEARCHER programs (

Computer Lab: You will learn how to use AlphaFold2 to predict protein structures through hands-on exercises, gaining practical experience in applying advanced AI techniques to biological systems.