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CV

• Date of birth :1984
• Degrees :
  2014 - PhD in computer science and systems biology (University of Rennes 1)
  2011 - Master in fundamental computer science (ENS Lyon, Université Claude Bernard Lyon 1)
  2010 - Master in biological systems modeling (University of Rennes 1)
  2008 - Bachelor's degree in Cellular Biology, Genetics, Microbiology and Animal Physiology (University of Rennes 1)

• Carreer  :
  2008 - Bioinformatics internship (UMR 6290): MIPDB, a relational database dedicated to the MIP protein family
  2009 - Systems biology internship (Roscoff Biological Station): Modeling the protein translation initiation network in sea urchins
  2010 - Bioinformatics internship (University of Montreal): Annotation of a highly divergent mitochondrial genome using hidden Markov chains
  2011- Systems biology internship (UMR IRISA and Roscoff Biological Station): Reconstruction of a metabolic network of Ectocarpus siliculosus
  2011-2014 - PhD in computer science and systems biology (UMR IRISA and Roscoff Biological Station): Combinatorial completion for the reconstruction of metabolic networks, and application to Ectocarpus siliculosus, the model of brown algae
  2015-2017 - Postdoc in systems biology and biotechnology (Chalmers university, Sweden): Reconstruction and analysis of 24 metabolic networks of Penicillium with emphasis on their secondary metabolism

CONTACTS

Attachement : Team Metabolism

sylvain.prigent@inrae.fr

Tel +33 (0)5 57 12 25 40

RESEARCH TOPICS

My career at INRAE is centered around a particular question: Understanding how metabolism influences plant performance. As a bioinformatician and modeler, I chose to answer this question by using both bottom-up (explaining complex phenomena from their specific mechanisms) and top-down (predicting complex phenomena from large-scale datasets) modeling approaches while taking a close interest in the quality of the data and their metadata.

Concerning top-down modeling, I develop different techniques to predict phenotypes from omics data (mainly metabolomics) produced in the majority of the Bordeaux Metabolome platform. As predictive models allow the discovery of biomarkers characteristic of a phenotype, I lead a working group dedicated to the discovery of biomarkers within our UMR.

For bottom-up modeling, I focus on the reconstruction and study of metabolic networks at the genome scale in order to better understand the effect of different factors (such as the development of a fruit) on the metabolism from a global point of view, notably via the study of flux maps.

Both of these research approaches are largely based on data analysis, whether it be existing data or newly acquired data. To allow an efficient use or, even more, a reuse of the data produced, it is very important that these data are FAIR (Easy to find, Accessible, Interoperable and Reusable) and I am therefore greatly involved in this aspect of open science, notably within the Bordeaux Plant Science Major Research Program and MetaboHub.

PUBLICATIONS

Complete list of publications on the HAL-INRAE portal

INFORMATIONS COMPLEMENTAIRES 

https://orcid.org/0000-0001-5146-0347