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0:00
So the
title of this talk is
Systems Biology Graphical Notation.
My name is Huaiyu Mi.
I work at the Division
of Bioinformatics
at Tech School of Medicine in
University of Southern California.
0:15
So what is SBGN?
SBGN is a standard
graphical representation
of biochemical and cellular events.
It is an unambiguous way to
graphically describe and interpret
pathway network knowledge
by both computer and human.
It is a representation of
logical mechanistic models,
biochemical pathways, at
different levels of granularity.
It has a set of defined
symbols together with rules
such as semantics, syntax,
and also layout rules.
You can find detailed information
and the website listed here.
And today in this talk, I'm going to
focus on the specification of SBGN.
On the website you can
also find software support
and also a parallel project
called libSBGN, which
I'm not going to talk
about in this talk.
On the website you can also find
detailed technical specifications,
precise data models, and
growing software support.
I just want to emphasize
that I'm talking on behalf
of the large community and
this project has been developed
over eight years by a
very diverse community.
And so the work was not
done just by myself.
It's really it reflects the
work from the entire community.
1:29
So what is the motivations
to start this project?
1:34
So, this is a schematic
diagram showing
the general paradigms
for biochemical research.
We always start with the
biological hypothesis.
And then we design experiments
and run experiments
in nowadays in the post-genome era.
Most of the experiments we've done
are high throughput experiments.
So what you're going to again are
all the high density data results.
And then you use softwares
and tools and database
to analyze this results.
What you expect is you can get
some functional implications
from these results.
Once you get these
functional results,
oftentimes you're going to
postulate another hypothesis
and runs through this cycle again.
After several iterations at
the end, you will find probably
what you expect the cure for
a certain disease spread.
