Hello, my name is Walter Kolch,
I'm the Director of Systems Biology Ireland in
the Conway Institute for Biomolecular and Biomedical
Research at University College Dublin in Ireland.
My personal interest is in
signal transduction pathways and we use a lot of proteomics tool to map these pathways.
I'd like to welcome you to this overview talk on proteomic technologies and targets.
The talk is in four parts.
I'll start with an introduction stating and laying out the problem.
Then I'll talk about some challenges associated with it and some of the technologies,
how we can address these problems and at the end is a short part on data analysis.
So let's start with a brief look at the human genome versus the human proteome.
Humans have 24 chromosomes which contains three billion base pairs worth of DNA.
These contain about 23,000 genes which can encode for about 100,000 messenger RNAs,
and this increase is generated through
alternative splicing and alternative use of promoters.
This 100,000 messenger RNAs can generate an equal number of proteins,
so we're dealing with about a 100,000 proteins.
However, if we take into account the protein modifications like
phosphorylation and other post-translational modifications
which occur once the proteins are made,
we actually deal with between half a million and
1.5 million different functional entities at the protein level.
So we have a huge increase in complexity as we move from the genome to the proteome.
So why then should we even bother about the proteins if they are so complicated?
The answer actually is fairly simple.
If you look at these two organisms,
a caterpillar and a butterfly,
they share the same genome but they have a different proteome.
So proteins are important because they can actually determine the phenotype.