The UNIVERSITY OF EDINBURGH
SCHOOL OF MATHEMATICS
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Date: Friday 23 November 2012 at 3pm
Location: 5326 JCMB
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Silvia Liverani (Imperial College London)
"A new Bayesian Dependence Model for Regulatory Networks"
Abstract
The usual assumption for clustering is that observations in the same
cluster share the same expression profile - accounting for measurement
error - and are expressed independently of observations outside their
own cluster. However, when searching over certain types of data, it is
unrealistic to assume independence between clusters as, for instance, in
the context of microarray experiments, it is well known that genes
belong to regulatory pathways and activate and inhibit each other. In
this talk we present a formal methodology for developing the semantics
of new Gaussian graphical models so that these are customised to be
faithful to a given scientific domain. This new class of models is
designed to utilize as much as possible the convenient separation
properties of a Bayes cluster model whilst continuing to respect the
types of dependence that scientists might conjecture exist. We
demonstrate how this class of models can be generalized to encompass
more credible deterministic functional dependence structures associated
with regulation. We show that it is possible to search over a large
number of different hypothesized regulation models, just as in Bayes
cluster models, and we interpret the results in a causal framework that
provides the scientist with a new hypothesis-generating tool. We
demonstrate the efficacy of these methods on a class of circadian models
where interest focuses on the regulatory relationships between different
genes. Each member in the class can be evocatively labelled by a
regulation graph closely resembling in its semantics the graphical
representations of regulation familiar to biologists. This is joint work
with Jim Q. Smith (University of Warwick).
There will be tea and coffee after the talk.
The seminar website (in google calendar):
http://www.maths.ed.ac.uk/events/statistics
This seminar series is a part of Maxwell Institute seminar series.
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