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Hello, everyone. My name is Christoph Steinbeck.
I'm a professor for Analytical Chemistry,
Cheminformatics and Chemometrics at the Friedrich Schiller University in Jena,
in Germany, and I'm also a visiting faculty
at the European Bioinformatics Institute in Cambridge,
in the United Kingdom.
Today, I'm going to speak about FAIR data in metabolomics.
This talk is part of a whole series of lectures on computational metabolomics,
and in order to understand it best,
I would encourage you to listen to the introductory talks on metabolomics beforehand.
Metabolomics is one of an ever growing number of -omes.
It is one of the youngest of those -omes and
many aspects which are already well-established in
other omics technologies are still under development in
metabolomics such as aspects of standards,
development, and data sharing.
Metabolomics complements information from genomics and proteomics.
Since the metabolism can be seen as an end point
of information processing in biomolecular systems,
the metabolome is at least partly influenced by the genome and gene expression.
Many of its aspects, however,
are directly influenced by external stimuli such as the food we eat and much more.
This is what I like to call the phenome-exposome conundrum.
The metabolome is a molecular phenotype which
reflects a very large number of external influences under which an organism develops.
These external influences include lifestyle,
what we eat, the fact that we age,
how we exercise or don't,
the diseases that we get,
the drugs we take, and,
of course, our inherited genetics.
Those external influences are nowadays subsumed under the name exposome.