7th edition of the Winter School on Algorithms in Structural Bioinformatics (AlgoSB):

Machine Learning Methods to Analyze and Predict Protein Structure, Dynamics and Function
Apprentissage machine pour la prédiction de structure, dynamique et fonction des protéines

8 – 12 November 2021

Scientific Committee

Frédéric Cazals (Inria Sophia-Antipolis-Méditerranée)
Isaure Chauvot-de-Beauchêne (LORIA-CNRS)
Juan Cortés (LAAS-CNRS)
Yann Ponty (Ecole Polytechnique)
Charles H. Robert (LTB-CNRS)

Program Committee

Frédéric Cazals (Inria Sophia-Antipolis-Méditerranée)
Cecilia Clementi (Free University of Berlin)
Juan Cortés (LAAS-CNRS)
Sergei Grudinin (LJK-CNRS)
Thomas Schiex (MIAT-INRAE)


The Algorithms in Structural Bioinformatics (AlgoSB) school focuses on novel or recent approaches in structural bioinformatics in the largest sense. Leading researchers from institutes around the world are invited to provide lectures together with hands-on practical courses. A fundamental goal of the school is to facilitate an algorithmic view of these ideas in order to identify new research directions.
AlgoSB is aimed at bringing together scientists from different disciplines (computer science, biophysics, biochemistry, mathematics, …) in a pleasant setting amenable to learning new approaches and creating synergies for future work.

The focus of AlgoSB 2021 is « Machine Learning Methods to Analyze and Predict Protein Structure, Dynamics and Function » (more details are provided on the lectures page).

The AlgoSB school is open to students and researchers wishing to integrate new theoretical approaches and methodologies into their research or to extend them in new directions. The school is open to senior and junior scientists from academia and industry as well as PhD students and postdocs. A maximum of 40 participants will be selected. More details are provided on the registration page.

Previous editions:


To kick things off, each participant is expected to provide a 5-minute presentation of their research interests on Sunday evening.
The morning sessions (Monday to Friday, starting at 9 a.m.) will be devoted to the following lectures:

Monday: Bettina Keller and Cecilia Clementi, Learning models of complex dynamics from simulation data
TuesdayTony Lelièvre and Gabriel StoltzConstructing collective variables using Machine Learning and free energy biased simulations
WednesdaySergey Ovchinnikov, Unified framework for understanding and evaluating generative sequence models
Thursday: M. Weigt, Wandering through sequence space : data-driven landscapes and protein evolution
Friday: Sergei Grudinin and Elodie Laine, Machine learning in the post CASP14 era : from protein structure to protein interactions



Ecole thématique