Teresa Przytycka, NIH - Computational Biology: From Genotype to Phenotype




Uploaded by IRPNIH on 14.12.2012

Transcript:
>> My name is Teresa Przytycka,
and I am a senior investigator here at National Center
for Biotechnology Information.
My group is a purely computational group.
We don't do any wet lab experiments,
but rather we do experiment with computers.
We collaborate a lot with experimental biologists here
at NIH, and actually one of the main reasons for which I
like to be here is that synergy that we have
with experimental groups.
What we focus on is the understanding of the variability
of the molecular system.
Of course, this is a very big topic, so in particular we would
like to understand the relationship,
especially the causal relationship,
between changing entities.
Those may be molecules, may be expression,
may be some phenotypes.
Since many years people investigated how the genetic
changes correlate
with phenotypic changes such as height.
Now, with the new data and with the new computational tools,
we are beginning to look more deeply,
not only what is the correlation, but trying to fill
that gap and think what really is happening between the changes
in genotype, eventually to how it changes the phenotype.
So we like to look at molecular structure, at network,
at dynamics, and at population.
So we like to take this multidimensional perspective
and, what I will say, a multiscale view
of biological systems.
In some way, I move towards computational biology by,
I would say, a little bit by accident.
So one of the questions that I'd been working on was related
to studies of tree-like structures that are useful
to guide certain types of computations.
And one of now my colleagues,
but then I didn't know the person, came and said, "Oh,
you are working on trees.
How about you look into this problem I have related
to comparing evolutionary trees?"
And that was the first problem
that was a biological problem that I looked at.
I really, you know, then didn't have much knowledge how those
trees were constructed to start with, but I became even more
and more interested in the opportunities
to apply those algorithmic tools, algorithmic knowledge
that I had, to biological systems.