MFSearcher

MFSearcher predicts elemental compositions from accurate mass values derived from high-resolution mass spectrometry to support metabolite annotation in metabolomics.

Key Features:

• Database-driven approach: Uses a relational database of pre-calculated elemental compositions with fixed kinds and numbers of atoms to avoid redundant formula evaluations.
• High-speed performance: Produces search times at least 109× faster than HR2, with SSD-based improvements of 488× at 5 ppm and 1833× at 0.1 ppm.
• Scalability across platforms: Maintains significant speed advantages over HR2 on lower-spec systems (e.g., Windows XP PC) where HR2 requires higher-spec hardware.
• RESTful API implementation: Implemented using Java, MySQL, Apache, and Tomcat and exposed as a RESTful web service.

Scientific Applications:

• Metabolite annotation: Predicts elemental compositions from high-accuracy mass spectrometry data to aid identification of metabolites.
• Pathway characterization: Supports identification and characterization of metabolic pathways by providing elemental composition candidates for detected masses.

Methodology:

Queries a relational database of pre-calculated elemental compositions using accurate mass values as input, eliminating redundant calculations by relying on fixed atom kinds and counts.