Journal Article

SIRIUS: decomposing isotope patterns for metabolite identification<sup>†</sup>

Sebastian Böcker, Matthias C. Letzel, Zsuzsanna Lipták and Anton Pervukhin

in Bioinformatics

Volume 25, issue 2, pages 218-224
Published in print January 2009 | ISSN: 1367-4803
Published online November 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn603

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Motivation: High-resolution mass spectrometry (MS) is among the most widely used technologies in metabolomics. Metabolites participate in almost all cellular processes, but most metabolites still remain uncharacterized. Determination of the sum formula is a crucial step in the identification of an unknown metabolite, as it reduces its possible structures to a hopefully manageable set.

Results: We present a method for determining the sum formula of a metabolite solely from its mass and the natural distribution of its isotopes. Our input is a measured isotope pattern from a high resolution mass spectrometer, and we want to find those molecules that best match this pattern. Our method is computationally efficient, and results on experimental data are very promising: for orthogonal time-of-flight mass spectrometry, we correctly identify sum formulas for >90% of the molecules, ranging in mass up to 1000 Da.

Availability: SIRIUS is available under the LGPL license at http://bio.informatik.uni-jena.de/sirius/

Contact: anton.pervukhin@minet.uni-jena.de

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  5735 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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