Qlife Quantitative Biology Spring School "Cell Dynamics in Developmental Systems"
Master in Life Science, ENS
BIO-Q-Qlife Spring School | Cell Dynamics in Developmental Systems
Year and Semester : M2 | S2
Where : Biology department, ENS
Duration : 1 week (March 31th –April 4th, 2025)
Credits : 3 ECTS`
Maximum class size : 25 students
This course is open to external students ->Contact
Coordination
Patrick Charnay, Biology Department, ENS
Chairman of the scientific committee :Yohanns Bellaïche, Institut Curie, France
Keywords
Deep learning-based image analysis | mechanical forces | genetic networks | single cell transcriptomics | spatial transcriptomics
Course prerequisites
Basic experience in file manipulation under Unix/Linux and coding ability in Python or R. Attendance is competitive (25 participants) and open to M2 and PhD students, postdocs, engineers and junior scientists with backgrounds in life science, physics, chemistry, computer science and mathematics and a strong interest in Developmental Biology.
Course objectives and description
Aims and themes : Recent technological developments in sequencing, imaging and image analysis have granted access to unprecedented temporal and spatial resolution of gene expression, cell dynamics and morphological features.
The Qlife program in Quantitative Biology of the PSL University organizes a spring school that will cover these emerging approaches through a series of lectures and digital workshops, using datasets from Drosophila, ascidians and mammals. Dynamic, quantitative analysis of tissue development will be performed through the combination of image analysis (deep learning-based segmentation, cell tracking, registration) with multiscale analysis of forces and modeling. These data will be integrated with the output of single cell and spatial transcriptomic analyses to provide an unprecedented combined view of cell location, morphology, interactions, migration, expression pattern and fate.
Organisation : Each day will include two introductory lectures in the morning, followed by digital workshops in the afternoon (on most days, the student can choose between two workshops). The evenings will include keynote speaker seminars and poster presentations by the students.
Common lunches and dinners with the speakers and instructors will foster informal discussions.
Assessment of M2 students :
After the course, students requiring a mark will write a written report on two of the computer tutorials, which will be assessed by the instructors.
Course material
The course will include introductory lectures, a series of hands-on computer tutorials run by experts in the field, seminars from prestigious researchers. In poster sessions, the students will have the opportunity to present their research and to obtain feedback from teachers.
Application Deadline
January 19th, 2025
Registration fees
150 € (fees cover food and lodging from Monday morning to Friday afternoon. Some travel grants will be available).
Application procedure
Register through this link https://forms.office.com/e/zmcfDKmqMt.
In addition, provide a CV, a motivation letter (including justification for travel grant if requested) and a supporting letter from a supervisor with “Qlife Cell Dynamics School 2025_LASTNAME” as subject header to Melissa.Dewulf chez curie.fr
Speakers and Instructors
James Briscoe, London
Florence Cavalli, Paris
Kate Mc Dole, Cambridge UK
Alessandro De Simone, Geneva
Geneviève Dupont, Brussels
Emmanuel Faure, Montpellier
Eileen Furlong, Heidelberg
Lucie Gaspard-Boulinc, Paris
Vincent Laville, Paris
Patrick Lemaire, Montpellier
Adrien Leroy, Paris
Lorette Noiret, Paris
Jean-Yves Tinevez, Paris
Pavel Tomancak, Dresden/Brno
Hervé Turlier, Paris
Thierry Voet, Leuven
Members of the Scientific Committee
Yohanns Bellaiche
Jérôme Gros
Thomas Lecuit
Patrick Lemaire
Romain Levayer
Lorette Noiret
Iris Salecker
Denis Thieffry
Jean-Yves Tinevez
Hervé Turlier
Céline Vallot
Suggested readings
Rao A, Barkley D, França GS, Yanai I. Exploring tissue architecture using spatial transcriptomics. Nature. 2021 Aug ;596(7871):211-220. doi : 10.1038/s41586-021-03634-9. Epub 2021 Aug 11. PMID : 34381231 ; PMCID : PMC8475179.
Hallou A, Yevick HG, Dumitrascu B, Uhlmann V. Deep learning for bioimage analysis in developmental biology. Development. 2021 Sep 15 ;148(18):dev199616. doi : 10.1242/dev.199616. Epub 2021 Sep 7. PMID : 34490888 ; PMCID : PMC8451066.
Goodwin K, Nelson CM. Mechanics of Development. Dev Cell. 2021 Jan 25 ;56(2):240-250. doi : 10.1016/j.devcel.2020.11.025. Epub 2020 Dec 14. PMID : 33321105 ; PMCID : PMC8177046.