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In the last talk,
we went over looking at
the gene expression in detail and the comparative ENCODE resource,
looking at non-coding transcription,
looking at how things could be clustered.
In this part, we're going to integrate gene expression with
other types of activity on the genome, particularly activity related to
the openness or closedness of the chromatin and also the activity of
various regulatory factors binding to the DNA and turning things on and off.
And we're going to try to make models that interrelate the openness to the chromatin,
for instance, to the gene expression.
We're also going to relate the factor binding to
the gene expression in the framework of statistical models.
And that's going to be these applications three and four,
which I'll go on to right now.
So now we're going to move onto the third application,
the building these models.
So the motivation is gene transcription,
this is a fundamental process of gene transcription.
Even though it's a very involved process,
it sort of has to do with factors binding upstream of the gene,
kind of opening up the chromatin,
and the chromatin, as you think of it, sort of the DNA wrapped around these spools,
and kind of opening it up,
and then the gene being out read by a polymerase.
And the open or closedness of the chromatin is often indicated
by what's called histone modifications.
And what we want to do, since we have a lot of data
on the openness or closedness of the chromatin and the factor binding,
we want to see if we can build a model that relates all these things together;
And in building the model,
it shows that we really understand the process.