Adriano Rutz

ChEBI-N performs ontology-based enrichment analysis on metabolomics data, identifying enriched chemical classes and demonstrating improved results with organism-specific backgrounds.

The paper shows that EPS from chitin degradation influences microbial community diversity by supporting different consumer types through sequential breakdown.

The paper develops an untargeted method to analyze plant extract taste and chemical composition, confirming bitterness in Swertia chirayita extract is due to iridoids and highlighting other compounds contributing to taste complexity.

The paper curates LC-MS/MS data from plant extracts to create a taxonomically focused database for exploring plant-derived molecules.

The paper introduces the Bioregistry, an open metaregistry that integrates and expands existing biomedical entity registries to improve interoperability and data reuse.

Inventa identifies chemically novel natural products in plant extracts by integrating mass spectrometry data and literature reports, demonstrating its utility with a Celastraceae family example.

The paper introduces the LOTUS initiative, which curates and shares 750,000+ structure-organism pairs via Wikidata to improve data interoperability and knowledge management in natural products research.

The paper enhances metabolite annotation confidence by integrating taxonomic information into spectral matching scores, improving recall and precision of annotation tools.