MetaboLinkAI combines a metabolomics knowledge-graph hub with artificial intelligence and machine learning. The project will make metabolomics data easier to query, interpret and reuse while supporting connections among spectra, molecules, biological samples and contextual knowledge.
Pierre-Marie Allard and the COMMONS Lab at the University of Fribourg participate in the consortium, contributing expertise in computational metabolomics, natural-products research and linked open data. This work is closely aligned with DBGI’s effort to organise chemical and biological observations as open, reusable knowledge.
More information is available on the SNSF grant page .
