Computational Metabolomics: Identification, Interpretation, Imaging (Dagstuhl Seminar 17491)

Abstract

Metabolites are key players in almost all biological processes, and play
various functional roles providing energy, building blocks, signaling,
communication, and defense. Metabolites serve as clinical biomarkers for
detecting medical conditions such as cancer; small molecule drugs
account for 90% of prescribed therapeutics. Complete understanding of
biological systems requires detecting and interpreting the metabolome in
time and space. Following in the steps of high-throughput sequencing,
mass spectrometry (MS) has become established as a key analytical
technique for large-scale studies of complex metabolite mixtures.
MS-based experiments generate datasets of increasing complexity and size.

The Dagstuhl Seminar on Computational Metabolomics brought together
leading experts from the experimental (analytical chemistry and biology)
and the computational (computer science and bioinformatics) side, to
foster the exchange of expertise needed to advance computational
metabolomics. The focus was on a dynamic schedule with overview talks
followed by break-out sessions, selected by the participants, covering
the whole experimental-computational continuum in mass spectrometry.
Particular focus in this seminar was given to imaging mass spectrometry
techniques that integrate a spacial component into the analysis, ranging
in scale from single cells to organs and organisms.