Sylvain Prigent

This study uses predictive metabolomics to link plant biochemical diversity with ecological strategies and physiological traits across 74 species.

This study uses predictive metabolomics to identify leaf metabolic signatures linked to floral traits in Camellia, finding distinct metabolite sets for flower colour and form with higher prediction accuracy for colour.

MetaNetMap automates mapping of metabolomic annotations onto genome-scale metabolic networks through direct, conversion-table-bridged and partial identifier matching, reproducing 311 mappings from a Parkinson's disease study.

The paper investigates how constrained temperatures affect sweet cherry flower bud dormancy, identifying a shallow dormancy stage induced by cold deprivation through transcriptomic analysis.

The paper presents rhto-GEM, the first genome-scale metabolic model of Rhodotorula toruloides, which accurately predicts growth and identifies genetic targets for improving lipid production.