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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Sparse Gaussian graphical models for dynamic gene
regulatory networks - Veronica Vinciotti (Brunel U
niversity)
DTSTART;TZID=Europe/London:20161214T111500
DTEND;TZID=Europe/London:20161214T120000
UID:TALK69522AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/69522
DESCRIPTION: Co-authors: Luigi Augugliaro (Uni
versity of Palermo)\, Antonino Abbruzzo (Univers
ity of Palermo)\, Ernst Wit (University of Groni
ngen)
 \;
In this t
alk\, I will present a factorial Gaussian graphica
l model for inferring dynamic gene regulatory net
works from genomic high-throughput data. The mode
l allows including dynamic-related equality constr
aints on the precision matrix as well as imposing
sparsity constraints in the estimation procedure
. I will discuss model selection and present an a
pplication on a high-resolution time-course microa
rray data from the Neisseria meningitidis bacteri
um\, a causative agent of life-threatening infect
ions such as meningitis. The methodology described
in this paper is implemented in the R package sg
lasso\, freely available from CRAN.
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
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