Hello. My name is Fabien Jourdan.
I'm a Senior Research Scientist at
the French Agronomic Research Institute in the South-West of France, Toulouse.
Today, I'm going to talk about
Metabolomics Data Analysis in the context of Metabolic Networks.
More generally, you will see that these data,
they can also be also kind of omics data that you can put in these networks.
So, it would be a brief overview just to give you
a broad idea about what you can do with these networks.
I will start with a little station about
Isaac Asimov saying the most exciting phrase to hear in science,
the one that heralds new discoveries,
is not Eureka but that's funny.
The point here is that the bioinformatics,
what we are doing in bioinformatics is just suggesting solutions.
We don't give final answers.
We provide some clues to the biologist about potential solution based on their data.
My point here and I will say that again is that we rely on the data and we cannot
100 percent sure that we provide
the perfect answer but we try to give good directions to that.
So, bioinformatics is basically a science of
recommendation and that's what I'm going to exemplify with the networks.
So, the first question I'm going to address and the main question is how can we
help in interpreting the metabolomics data in the context of metabolic networks?