Metabolomics is the study of small molecules, or metabolites, present in cells, tissues, or biofluids. The analysis of the metabolome involves identifying and quantifying these metabolites to gain insights into the metabolic processes occurring within an organism.

Metabolomics can provide valuable information about an organism's physiological state, disease progression, response to treatments, and environmental exposures. By comparing the metabolite profiles of different samples, we try to identify biomarkers for various conditions and gain a better understanding of metabolic pathways and their regulation.

We are using several analytical techniques in metabolomics, including mass spectrometry (MS), ion mobility mass spectrometry (IM-MS) and 1D- and 2D-gas- and liquid chromatography. These techniques allow for the detection and quantification of a wide range of metabolites, including amino acids, lipids, sugars, and organic acids.

Data analysis in metabolomics typically involves processing raw data from analytical instruments, identifying metabolites based on their mass spectra, and performing statistical analyses to compare metabolite profiles between samples. Advanced computational tools are often used to integrate and interpret large datasets generated in metabolomics studies. We are developing new software tools to automate the data analysis workflow as much as possible in order to achieve a higher throughput.