The project will develop computational approaches for studying natural products, metabolomes and chemical diversity. It will combine mass spectrometry, computational metabolomics, machine learning and statistical methods to investigate patterns in the chemistry produced by living organisms.
Its focus on chemodiversity and reusable chemical knowledge is closely aligned with DBGI’s broader effort to document plant chemistry and connect molecular observations with biological context. The work is based in the COMMONS Lab at the University of Fribourg.
More information is available on the SNSF grant page .
