Actualité - Financement
Interdisciplinary Laureats 2023
In 2023, we have funded 5 interdisciplinary projects, four of them at €90k and the fifth at €40k. These projects will foster fruitful new collaborations between teams within the PSL-Qlife Institute. Congratulations!
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Projects funded in 2023
- Pierre Barraud (IBPC) & Guillaume Bouvignies (ENS) - Conformational dynamics in tRNAs: influence of post-transcriptional modifications I This project seeks to investigate how tRNA molecules are structurally and dynamically altered by modifications that occur after transcription. Utilizing NMR spectroscopy, our goal is to offer precise and measurable insights into the tRNA maturation process at the atomic scale.
- François Mallard (IBENS) & Ingrid Lafontaine (IBPC) - Role of structural variants in adaptation to novel environments I Large chromosomal duplications, deletions, or inversions are a major source of evolution such as speciation events or cancer development. We will track structural variants' role during experimental evolution in nematodes by combining genetics and comparative genomics.
- Koyomi Nakazawa (Institut Curie) - Structural thermodynamics study on biological condensates I This project is aimed to understand quantitatively the formation pathway of protein condensates, and their further evolution to amyloid fibril formation causing neurodegenerative diseases. This fundamental knowledge might help us to develop new strategies to fight those diseases.
- Benoit Sorre (Institut Curie) & Vincent Hakim (LPENS) - In vitro and in silico modeling of spinal tissue patterning by static and dynamic morphogen gradients I We want to use microfluidics to generate spinal cord tissues in vitro with the correct cellular composition and organization. Doing so, helped by modelling and simulations, we expect to learn how the spinal cord is made in the embryo and how to generate functional spinal tissue from Stem Cells
- Marie-Hélène Verlhac (Collège de France) & Auguste Genovesio (IBENS) - Phase Microscopy Artificial Intelligence for Fertility I Our basic research project, using in part artificial intelligence, will qualitatively and quantitatively estimate oocyte stores in a non-invasive manner for robust selection of the best fit ones. Phenotyping oocytes without compromising their development is of direct utility for both academia and clinics.