MINE

MINE expands biochemical networks to generate candidate metabolite structures for identifying unannotated peaks in untargeted metabolomics.

Key Features:

• Expanded Biochemical Coverage: Incorporates a new set of biochemical transformation rules that cover 93% of MetaCyc reactions (compared to 25% in MINE 1.0), producing a 17-fold increase in database size.
• In silico Network Expansion: Generates hypothetical metabolite structures by applying biochemical transformation rules derived from MetaCyc reactions.
• Increased Matching Capability: Provides a 40% increase in the number of compounds in the MINE database that match unannotated peaks from untargeted metabolomics datasets.

Scientific Applications:

• Untargeted Metabolite Identification: Generate candidate structures for unannotated mass spectrometry peaks in untargeted metabolomics datasets.
• Metabolic Pathway Analysis: Expand the set of potential pathway members and reaction products to inform systems biology investigations.
• Pharmacology and Environmental Metabolomics: Support discovery and characterization of xenobiotic, drug-related, and environment-derived metabolites.

Methodology:

Expand known biochemical networks by applying transformation rules derived from MetaCyc reactions to generate hypothetical metabolite structures for matching against untargeted metabolomics peaks.