The event aims to promote the exchange of scientific ideas, discuss the latest discoveries and emerging topics, and foster the education of young scientists.
Recent AI-driven techniques have become available to explore protein structures, from prediction and analysis to protein design. The availability of a large amount of protein structure data makes the extensive use of ML and AI methods in a wide range possible. The development of AlphaFold and many other tools show the potential but also the challenges in the field not only determined by data handling and storage but also by the integration of data that differ in quality and quantity due to experimental settings. As this multi-disciplinary field is rapidly developing there is a great need for knowledge exchange and discussions bringing together scientists and students from biology, biochemistry, bioinformatics, physics, and computer science.
At the meeting, emerging concepts will be discussed by leading international experts covering the different facets of the field. The topics include theory & tool development, machine learning in structural biology, AI-based structure prediction & integrative modeling, and AI-driven protein design. Critical discussions of state-of-the-art research will allow us to together chart future developments at the interface of basic science and applications, while fruitful scientific exchange of ideas will help inspire young scientists in their future research endeavors in this rapidly developing field.
Topics
- Theory & Tool Development
- Machine learning in structural biology
- AI-based structure prediction & integrative modeling
- AI-driven protein design
Scientific Organizing Committee
- Janosch Hennig, University Bayreuth, Germany
- Ina Koch, Goethe University, Germany
- Birte Höcker, University Bayreuth, Germany
Event Details
