Dear All,
I am pleased to announce that the following seminars will take place
next Friday afternoon (March 2nd). All welcome. Instructions for virtual
contact are given after the abstracts.
Friday, March 2nd, 2-4pm, GLG043
2pm
Using a network model to explore the impact of a reduction in
concurrency on HIV incidence in Uganda
Katie O'Brien (National Cancer Registry, Cork)
3pm
Sparse factor models for gene interaction networks.
David Causeur (CNRS, Rennes)
(joint work with Yuna Blum)
Using a network model to explore the impact of a reduction in
concurrency on HIV incidence in Uganda
Abstract
Concurrent partnerships have been implicated in the high endemic HIV
prevalence that is observed in sub-Saharan Africa.
However, evidence is limited and previous models have mainly focussed on
the potential role of concurrency in the initial spread of African HIV
epidemics. We wanted to examine the possible effects of a reduction in
concurrency in well established, generalised epidemics, typical of
countries in Eastern and Southern Africa. We used a dynamic network
model where disease may be transmitted at the individual level. In
particular, we explored the effects of "re-wiring" the network on HIV
incidence.
Sparse factor models for gene interaction networks.
Abstract
Inference on gene regulatory networks from high throughput expression
data is one of the most challenging issues in systems biology. Such
interaction networks are needed to give more insight into the functional
characterization of sets of genes. Estimating such networks has to deal
with both the high dimension of gene expression data and the sparsity of
the interaction structure.
In the Gaussian Graphical Models settings, expression profiles are
assumed to be normally distributed and partial correlations are viewed
as gene interaction parameters. Inferring on networks consists therefore
in estimating the partial correlation structure, or equivalently the
inverse covariance matrix of the expression profile under sparsity
conditions. As proposed by some authors, this can be achieved by
regularization of the usual estimating procedures minimizing the
deviance using a LASSO type penalty. In this talk, we assume a sparse
factor model for the covariance of gene expressions. We propose a
regularized EM algorithm for the partial correlation structure with a
LASSO penalty on the factor structure induced on the inverse covariance
matrix. We show that combining a dimension reduction method to sparse
estimation improves the performance of some existing methods.
David Ramsey,
There are three ways to connect to the HEAnet MCU for making multipoint
calls and you should forward this information to your contact in NUIG.
1. Using the GDS Number.
The GDS number for the one of the UL virtual meeting rooms is
003530110051108.
This virtual meeting room does not require a PIN for access.
2. Using the MCU gateway IP Address.
The IP address of the MCU is 193.1.31.196
To access the UL virtual meeting room,
either use the # button on the VC remote control to access the keypad
and dial 108#
or follow the voice instructions from the MCU to use the FAR control and
the up or down controls and the select button to select "University of
Limerick" from the list.
3. Using ISDN.
The ISDN number for the MCU is +353 (0)1 4490889.
The MCU gateway will answer and request that the extension be dialled
followed by the # sign, in this case 7108#.
The ISDN connection can be used for voice only calls from a telephone to
a multipoint videoconference.
Michael Chapman
VideoConference Suite 1, GLG043
Audio Visual Services, ITD
Glucksman Library Building
University of Limerick
Limerick
IRELAND
Tel: +353 61 202189
Fax: +353 61 202938
email: [log in to unmask]
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