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SUMMARY:Sparse Gaussian graphical models for dynamic gene regulatory netwo
 rks - Veronica Vinciotti (Brunel University)
DTSTART:20161214T111500Z
DTEND:20161214T120000Z
UID:TALK69522@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>         Co-authors: Luigi Augugliaro 		(University of P
 alermo)\, Antonino Abbruzzo 		(University of Palermo)\, Ernst Wit 		(Unive
 rsity of Groningen)        <br></span><span>&nbsp\;<br>In this talk\, I wi
 ll present a factorial Gaussian graphical model for  inferring dynamic gen
 e regulatory networks from genomic high-throughput  data. The model allows
  including dynamic-related equality constraints on  the precision matrix a
 s well as imposing sparsity constraints in the  estimation procedure. I wi
 ll discuss model selection and present an  application on a high-resolutio
 n time-course microarray data from the  Neisseria meningitidis bacterium\,
  a causative agent of life-threatening  infections such as meningitis. The
  methodology described in this paper  is implemented in the R package sgla
 sso\, freely available from CRAN.</span>
LOCATION:Seminar Room 1\, Newton Institute
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