Computational Project Manager

Florent Guinot

Data Science

“As a data scientist with a biological background, I thrive using my skills and knowledge in data science to bring innovative therapeutic solutions to patients.”

Your role at Institut Roche and brief presentation of your professional background:

I joined Institut Roche in 2021 as a Scientific Project Manager in computational mathematics. My role is to develop and manage projects in data science to accelerate the innovation in biomedical research. I have a data science profile with several years of experience in both public and private sector combined with a background in biology thanks to my agricultural engineering degree.

My Focus at Institut Roche:

My focus is to manage projects and partnerships that make use of computational mathematics to drive innovation on biomedical research in several therapeutic areas (Neurodegenerative disease, oncology, immunology, blood diseases). I am also involved in research projects to provide insights in data mining, statistical analysis and machine learning.

  1. Misra N, Clavaud C, Guinot F, Bourokba N, Nouveau S, Mezzache S, Palazzi P, Appenzeller BMR, Tenenhaus A, Leung MHY, Lee PKH, Bastien P, Aguilar L, Cavusoglu N. Multi-omics analysis to decipher the molecular link between chronic exposure to pollution and human skin dysfunction. Sci Rep. 2021 Sep 15 ;11(1) :18302. doi : 10.1038/s41598-021-97572-1.
  2. Leung, M.H.Y., Tong, X., Bastien, P. et al. Changes of the human skin microbiota upon chronic exposure to polycyclic aromatic hydrocarbon pollutants. Microbiome 8, 100 (2020). https://doi.org/10.1186/s40168-020-00874-1
  3. Guinot, F., Szafranski, M., Chiquet, J. et al. Fast computation of genome-metagenome interaction effects. Algorithms Mol Biol 15, 13 (2020). https://doi.org/10.1186/s13015-020-00173-2
  4. Guinot, F., Szafranski, M., Ambroise, C. et al. Learning the optimal scale for GWAS through hierarchical SNP aggregation. BMC Bioinformatics 19, 459 (2018). https://doi.org/10.1186/s12859-018-2475-9
  5. Bouchet, AS., Laperche, A., Bissuel-Belaygue, C. et al. Genetic basis of nitrogen use efficiency and yield stability across environments in winter rapeseed. BMC Genet 17, 131 (2016). https://doi.org/10.1186/s12863-016-0432-z
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