An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites

Abstract

Since 2004, we have been developing a metabolite database concerning species-metabolite relations called KNApSAcK, which currently contains 49,165 species-metabolite relations incorporating 24,847 metabolites. In the present study, we report current status of KNApSAcK database and it's application to metabolomics fields and propose a new algorithm for detecting fragmentation patterns in a complicated mixture such as a plant tissue and a new scheme for analyzing spectral information leading to peak annotation of GC-MS spectra. When considering samples corresponding to a variety of species in addition to model species, KNApSAcK DB has strong potential for contribution to metabolomics research by way of applying it not only to simple metabolite search but also to further metabolomics analysis.