title: MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures.
abstract: BACKGROUND
  One-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.
  
  
  RESULTS
  We introduce a web server application, called MetaboHunter, which can be used for automatic assignment of 1H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunter's metabolite identification methods.
  
  
  CONCLUSIONS
  MetaboHunter is a freely accessible, easy to use and user friendly 1H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.
authors: Institute for Information Technology, National Research Council of Canada, Moncton, New Brunswick, E1A 7R1, Canada. dan.tulpan@nrc-cnrc.gc.ca
authors: Dan
authors: D
authors: Tulpan
authors: Serge
authors: S
authors: Léger
authors: Luc
authors: L
authors: Belliveau
authors: Adrian
authors: A
authors: Culf
authors: Miroslava
authors: M
authors: Cuperlović-Culf
mesh_terms: D020407:Internet; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D055432:Metabolomics / Q000379:methods*; D012984:Software