[CV] Marion Brandolini-Bunlon

Contact infos

• email : marion.brandolini-bunlon{at}inrae{dot}fr 
• tel : +33(0)4 73 62 46 76

As a statistician in the "metabolomics" component of the Metabolism Exploration Platform ("PFEM"), I am in charge of the statistical processing of data from research projects with a non-targeted metabolomics approach (pre-processing, statistical analyses, parametric or non-parametric, uni or multidimensional), in order to highlight the metabolites whose relative intensities vary between experimental groups to characterize phenotypes or identify biomarkers. I am also co-leader of the quality process "research and development" concerning data processing, and I design and develop tools, mainly with R software, for the integration of metabolomic data with other types of data, or to optimize the statistical methods used on the PFEM. Finally, I provide training in statistical methods applied to metabolomic data, including multi-block methods. In particular, I am a trainer and co-organizer of the ChemOmics school.

Missions

• organization of the preparation of metabolomic data for nutrition/health projects, statistical processing of data with the most appropriate statistical and computer tools, valorization of results.
• design, piloting, participation in the realization, dissemination and valorization of statistical tools (workflow, programs, packages with their documentation for the users) to integrate metabolomic data with other data, or to optimize statistical treatments.
• knowledge transmission and skills transfer (teaching, supervision of trainees).
• management of the "research and development" quality process concerning data processing.

Main publications

• Brandolini-Bunlon, M., Jaillais, B., Cariou, V., Comte, B., Pujos-Guillot, E., & Vigneau, E. (2023). Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics. Metabolites, 13(3), 373. https://doi.org/10.3390/metabo13030373
• Comte, B., Monnerie, S., Brandolini-Bunlon, M., Canlet, C., Castelli, F., Chu-Van, E., Colsch, B., Fenaille, F., Joly, C., Jourdan, F., Lenuzza, N., Lyan, B., Martin, J.-F., Migné, C., Morais, J., Pétéra, M., Poupin, N., Vinson, F., Thevenot, E., … Pujos-Guillot, E. (2021). Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men. EBioMedicine, 69. https://doi.org/10.1016/j.ebiom.2021.103440
• Imbert, A., Rompais, M., Selloum, M., Castelli, F., Mouton-Barbosa, E., Brandolini-Bunlon, M., Chu-Van, E., Joly, C., Hirschler, A., Roger, P., Burger, T., Leblanc, S., Sorg, T., Ouzia, S., Vandenbrouck, Y., Médigue, C., Junot, C., Ferro, M., Pujos-Guillot, E., … Herault, Y. (2021). ProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis. Scientific Data, 8(1), 311. https://doi.org/10.1038/s41597-021-01095-3 
• Brandolini-Bunlon, M., Pétéra, M., Gaudreau, P., Comte, B., Bougeard, S., & Pujos-Guillot, E. (2019). Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10), np. https://doi.org/10.1007/s11306-019-1598-y