ARISTO

ARISTO annotates Electron Ionization (EI) mass spectra from Gas Chromatography–Mass Spectrometry (GC-MS) with ChEBI ontology terms to enable chemical classification when exact spectral matches are unavailable.

Key Features:

• Ontology-Based Annotation: Maps EI mass spectra to the ChEBI (Chemical Entities of Biological Interest) ontology to assign chemical classes and terms.
• Non-Exact Match Capability: Provides meaningful ontology-level annotations when exact matches to reference spectra in curated libraries are not found.
• Input Format: Accepts EI mass spectra represented as mass-to-charge (m/z) ratios paired with intensity values.
• Statistical Evidence: Associates each suggested annotation with statistical support or confidence measures.
• Output Representation: Produces graphical and tabular representations of suggested annotations along with their statistical support.

Scientific Applications:

• Metabolite Identification: Assists in discovery and characterization of metabolites in biological samples using GC-MS EI spectra.
• Environmental Monitoring: Aids detection and classification of pollutants or small molecules in environmental samples.
• Pharmaceutical Research: Supports identification of potential bioactive small molecules relevant to drug discovery.

Methodology:

ARISTO accepts EI mass spectra as m/z and intensity pairs, uses algorithms to map the input spectrum to relevant entries in the ChEBI ontology to identify chemical classes or families, and outputs graphical and tabular results with associated statistical support.