Mégret Lucile

Welcome to my home page !

Version française

Contact

• lucile.megret@sorbonne-universite.fr

• Cassan B 617, 7 quai Saint Bernard 75005 Paris

Researches and teaching activities

I am Associate Professor (maîtresse de conférences) in Sorbonne Université in the BrainC team of laboratory B2A . You will find here an amazing poster that present the team ! Part of our results are available on the Biogemix platform.

Here is a detailed CV.

Research interest

My work focus on the mechanisms of brain resilience in neurodegenerative diseases. That is, the brain's ability to remain in a state of cellular adaptation and compensation to maintain its functions, without switching to mal-adaptive cellular responses and become symptomatic. In order to understand these mechanisms, I analyze large omics datasets using machine learning methods and mathematical modeling.

Teaching activity

I teach in Biomath division of UFR 927. My teachings cover statistics, deterministic modeling and programming.

Ph.D thesis

My Ph.D, supervised by Jean-Pierre Françoise and Frédérique Clément, is entitled Limits cycles explosions, qualitative analysis, numerical simulations and models. This work focused on the analysis of novel explosions of limit cycles (periodic orbits), which arise in the modeling of oscillations in biology.

To know more about my research and teaching activity:

• Publications and preprints
• Teaching activities

Selected/Invited talks at international conferences

• L. Mégret, Use of shape analysis concepts in machine learning to precisely analyze complex omics data, NSERM-JSPS Workshop, AI and big data approaches in precision medicine and health science, Yamaguchi University, December 2022, Japan.
• L. Mégret, Precision machine-learning identifies a new paradigm for therapeutic discovery in Huntington's disease: remodeling stress response to re-instate neuronal health and resilience, The 21st International Conference on Systems Biology (ICSB 2022), October 2022, Berlin Germany.
• L. Mégret, Precise machine learning suggest that brain cells facing a neurodegenerative insult are the subject of molecular decompensation and aging, 2nd Euro-Geroscience Conference, March 2022, Toulouse France.
• L. Mégret, Precise machine learning suggest that brain cells facing a neurodegenerative insult are the subject of molecular decompensation and aging, Groningen-Jena Aging Meeting (G-JAM), October 2021, remote.
• L. Mégret, miRAMINT: modelling RNA-seq time-series data through variable selection and surface matching narrows the implication of miRNAs in the brain of Huntington's disease knock-in mice,EMBO Workshop, Network inference in biology and disease, June 2019, Naples, Italy.

Communication en direction du publique

• Images des Mathématique's press review (in french) from 09/2021 to 01/2022.
• An article in the AHF gazette (in french).