We present a method for determining the sum formula of metabolites solely from their mass and isotope pattern. Metabolites, such as sugars or lipids, participate in almost all cellular processes, but the majority still remains uncharacterized. 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. Determination of the sum formula is a crucial step in the identifica- tion of an unknown metabolite, as it reduces its possible structures to a hopefully manageable set. Our method is computationally efficient, and first results on experimental data indicate good identification rates for chemical compounds up to 700 Dalton. Above 1000 Dalton, the number of molecules with a certain mass increases rapidly. To efficiently analyze mass spectra of such molecules, we define several additive invariants extracted from the input and then propose to solve a joint decomposition problem.

Decomposing metabolomic isotope patterns

Liptak, Zsuzsanna;
2006

Abstract

We present a method for determining the sum formula of metabolites solely from their mass and isotope pattern. Metabolites, such as sugars or lipids, participate in almost all cellular processes, but the majority still remains uncharacterized. 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. Determination of the sum formula is a crucial step in the identifica- tion of an unknown metabolite, as it reduces its possible structures to a hopefully manageable set. Our method is computationally efficient, and first results on experimental data indicate good identification rates for chemical compounds up to 700 Dalton. Above 1000 Dalton, the number of molecules with a certain mass increases rapidly. To efficiently analyze mass spectra of such molecules, we define several additive invariants extracted from the input and then propose to solve a joint decomposition problem.
9783540395836
bioinformatics, computational mass spectrometry, metabolomics, efficient algorithm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/391092
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