The MiFoBio 2025 thematic school will be held from Friday October 10 to Friday October 17 (shuttle departure).

After the 2021 post-confinement and 2023 GDR 20th anniversary editions, for which we chose to welcome more participants (390!), we’ll be welcoming a smaller number of participants (330) in 2025, while maintaining the same interdisciplinary approach to science and technology. As always, the program will be rich and varied, with a balance of lectures, seminars, round-table discussions and workshops covering a broad spectrum of topics.

MiFoBio will offer the following 6 teaching modules and seminars (this program is still being finalized; only guests who have confirmed their attendance are listed here):

Module 1: Marking strategies at different scales of life

Coordination : Marie Erard, Arnaud Gautier

• Mickael LIN, Stanford University (USA)
• Amy PALMER, University of Colorado Boulder (USA)
• Michelle FREI, ETH Zürich (Switzerland)
• Marc VENDRELL, University of Edinburgh (Scotland)

Module 2: Nanoscopy : the challenges of spatial and temporal quantification

Coordination : Sandrine Lévêque-Fort, Lydia Danglot

• Giuseppe VICIDOMINI, ITT Genoa (Italy)
• Francisco BALZAROTTI, IMP Vienna (Austria)
• Jorg BEWERSDORF, Yale University (USA)
• 4th course to be defined

Module 3: Analysis, simulation and modelling: a new paradigm with AI ?

Coordination : Aymeric Leray, Jean-Baptiste Sibarita

• Loic ROYER, Chan Zuckerberg Biohub San Francisco (USA)
• Flavie LAVOIE-CARDINAL, Laval Univ. (Quebec)
• 3rd course to be defined
• 4th course to be defined

Module 4: Multi-scale imaging of biological systems

Coordination : Rémi Galland, Gaëlle Recher

• Matthias LUTOLF, Roche Institute for Translational Biology, Basel (Switzerland)
• Timo BETZ, Goettingen Univ. (Germany)
• David LABONTE, Imperial College London (England)
• Laura BATTI, Wyss Center, Geneva (Switzerland)

Module 5: Physical measurements, control and handling – Mechanobiology

Coordination : Cécile Leduc, Renaud, Olivier

• Khalid SALAITA, Emory University, Atlanta, Georgia (USA)
• Iva TOLIC, Ruder Boskovic Institute, Zagreb (Croatia)
• Daria BONAZZI, Institut Pasteur, Paris (France)
• Pierre NASSOY, Bordeaux Univ. (France)

Module 6: Waves on living organisms: breakthrough strategies in life imaging

Coordination : Thomas Chaigne, Pascal Berto

• Alexander JESACHER, Medical University of Innsbruck (Austria)
• Amanda FOUST, Imperial College London (England)
• Chiara PAVIOLO, CEA-LETI, Grenoble (France)
• Hugo DEFIENNE, Sorbonne Univ., Paris (France)

Seminars:

• Maddy PARSONS, King’s College London (England)
• Vasilis NTZIACHRISTOS, Technical Univ. of Munich (Germany)
• Michelle DIGMAN, Univ. of California, Irvine (USA)
• Elisabeth HILLMAN, Colombia Univ. , New York (USA)
• Luke LAVIS, Janelia Farm Research Campus, Ashburn, Virginia (USA)
• Emmanuelle BAYER, Univ. Bordeaux (France)

Previsional schedule:

“Premodules for beginners” :

These courses are designed for people who do not have a basic knowledge of the relevant fields. These are optional courses, for which there will not be a huge number of places (maximum 15 people per course). Mifobio participants wishing to register will be invited to do so when they receive, directly by e-mail, a form designed to collect a set of information for the organization (arrival and departure times, accommodation, and therefore possible registration for a pre-module). These courses will a priori be given in French. The description is available below:

Cell biology basics – Delphine Muriaux & Gabriel Bidaux

The organism, whether plant or animal, is made up of billions of cells of different types and functions, which differentiate during development following fertilization. In this course, we will pay particular attention to the cell as a unit, defining its molecular aspects in general terms. We’ll describe the differences between eukaryotic and prokaryotic cells, their intracellular compartments (Nucleus, Reticulum, Golgi, Mitochondria, Endosomes…) and the notions of Membranes, Proteins, RNA and DNA, in size, numbers and color. Finally, we’ll look at transfection, transduction and infection, as tools for expressing fluorescent proteins in these cells and visualizing them by microscopy.

The organization of living organisms is constrained by the laws of chemistry and physics, and its study requires tools whose dynamic ranges and limits must be adjusted to the right dimensions. The second part of this course introduces the notions of space and time of processes from the molecular to the organismal scale.

Basic optics – Olivier Haeberlé

This pre-module introduces the basics of image formation in a conventional optical microscope and places them in the context of the various technologies that will be covered in greater depth in the modules (elementary geometrical optics, phase and polarization, diffractive optics and PSF, introductions to super-resolution and microtomography techniques).

Basic photophysics and chemistry for microscopy – Frédéric Bolze

This pre-module provides an overview of the various processes involved in light absorption and fluorescence, focusing on the properties of fluorophores useful in microscopy: absorption spectra, molar absorption coefficient, emission spectra, quantum yield, brightness, lifetime, fluorescence versus phosphorescence, reactions with the environment, bleaching, nonlinear optics and two-photon absorption, second harmonic generation). We’ll also take a brief look at the chemical reactions induced by light absorption (photoisomerization and decaging). The thread running through this pre-module will be a fluorescent probe that will be synthesized at MIFOBIO in the Chem-Lab, and we’ll be looking at the various stages involved in its design, synthesis, chemical and photophysical characterization, so that it can be used as a mitochondrial probe on the systems present at MIFOBIO.

Introduction to machine learning for image processing – David Rousseau

In this pre-module, we offer an introduction to machine learning for image processing. We will show the links with classical approaches to image analysis using convolutional filters, and gradually introduce the decision tree and convolutional neural network approaches. We will explain the principles of these methods, illustrate them on biological images and discuss the advantages and limitations of these machine learning methods. This module will enable participants to take advantage of modules including AI aspects during the rest of the school.