Ecole thématique AI4BioMed

7 avr. 2025, 08:00 → 9 avr. 2025, 20:00 Europe/Paris

Polytech Lyon

Spring School on AI and Machine Learning and their Applications to Biology and Health -  Université Lyon 1, La Doua, Villeurbanne, April 7-9 2025.

Artificial intelligence and machine learning are rapidly transforming our research activity in biological sciences and health. As a result, there is a critical need for making machine learning and AI accessible to everyone currently working in these scientific and applied domains.

 

To meet those challenges, the DIgitBioMed initiative proposes a 3-day spring school, April 7-9 2025, on machine learning and AI in Biological and Health sciences. This spring school will provide a basic introduction to machine learning, deep learning, AI, and their applications to biology and health.

 

In terms of the practical outline, the three days will consist of a combination of basic courses, hands-on sessions, conferences on principles and on applications, round-tables and discussions. Two parallel tracks of hands-on session will be proposed, depending on the level of skills in basic programming and in mathematics and statistics. This is meant to give everyone an opportunity to get an entry point to basic understanding and practical manipulations in machine learning and AI in research today.

 

Prerequisites: knowledge of scripting in either Python or R. Some acquaintance with biological and/or health related sciences (applicants can come from a math, stat or computer science background, but they should then either have at least some courses related to biology and/or health in their current training programs, or should be involved in at least some research activities related to biology and/or health). 

 

Eligibility: All MSc, PhD students, post-docs, permanent members are eligible. A priority will be given to MSc and PhD students of the masters, doctoral schools and laboratories associated with the DigitBioMed initiative. For more information about DigitBioMed, its programs and its member labs: https://graduate-plus.fr/digital-sciences-forbiology-and-health/

 

Registration is free but required by March 21, 2025.

 

Program

 

Monday, April 7, 2025 

 

09:00-9:30: Welcome 

09:30-10:30: Course 1 - Philippe Veber - Introduction and general principles

10:30-13:00: Hands-on session

 

13:00-14:00: lunch

 

14:00-15:00: Course 2 - Stefan Duffner - Neural architectures and learning design 1

15:00-16:00: Conference: Mohammed Sedki, Université Paris Saclay
Neural architectures for text data and healthcare applications.

16:00-18:00: Hands-on session

 

Tuesday, April 8, 2025

 

09:00-10:00: Course 3 - Stefan Duffner - Neural architectures and learning design 2

10:00-13:00: Hands-on session

 

13:00-14:00: lunch

14:00-15:00: Conference. Jeremy Kalfon, Institut Pasteur, Machine Learning for Integrative Genomics
scPRINT: pre-training on 50 million cells allows robust gene network predictions

 

15:00-17:00: Hands-on session

17:00-19:00: poster session and cocktail

 

Wednesday, April 9, 2025

 

09:00-10:00: Hands-on session. Follow up and Wrap up

10:00-13:00: Parallel hands-on session: applications

• TP1 - Using deep-learning to estimate epidemiological parameters from pathogen phylogenetic trees - Anna Zhukova (Institut Pasteur)
• TP2 - The autoencoder - Stefan Duffner (INSA Lyon)
• TP3 - Penalized splines for flexible modelling while limiting overfitting: application to survival analysis in cancer patients - Matthieu Fauvernier and Pascal Roy, (HCL, Université Claude Bernard)

 

13:00-14:00: lunch

 

14:00-15:00: Conference. Flora Jay, CNRS, Université Paris-Saclay, Laboratoire Interdisciplinaire des Sciences du Numérique 
Designing neural networks for population genetics

 

15:00-16:00: Course 4: Perspectives

 

 

Speakers

Flora Jay, Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique

https://flora-jay.blogspot.com/

Jeremie Kalfon, Institut Pasteur, Machine Learning for Integrative Genomics

https://www.jkobject.com

Mohammed Sedki, Université Paris Saclay

https://oncostat.github.io/

 

Teaching staff

Julien Barnier 

Bastien Boussau

Stefan Duffner 

Mathieu Fauvernier 

Nicolas Lartillot

Enzo Marsot

Anamaria Necsulea 

Pascal Roy

Philippe Veber

Anna Zhukova

 

Scientific Committee

• Julien Barnier: Laboratoire de Biométrie et Biologie Évolutive, Université Claude Bernard Lyon 1, CNRS.
• Stefan Duffner: Laboratoire d'InfoRmatique en Image et Systèmes d'information, INSA Lyon
• Nicolas Lartillot: Laboratoire de Biométrie et Biologie Évolutive, Université Claude Bernard Lyon 1, CNRS.
• Pascal Roy: Laboratoire de Biométrie et Biologie Évolutive, Université Claude Bernard Lyon 1, Hospices Civils de Lyon
• Philippe Veber: Laboratoire de Biométrie et Biologie Évolutive, Université Claude Bernard Lyon 1, CNRS

Registration: