skip to content

Sparse Gaussian graphical models for dynamic gene regulatory networks

Presented by: 
Veronica Vinciotti Brunel University
Wednesday 14th December 2016 - 11:15 to 12:00
INI Seminar Room 1


Co-authors: Luigi Augugliaro (University of Palermo), Antonino Abbruzzo (University of Palermo), Ernst Wit (University of Groningen)  
In this talk, I will present a factorial Gaussian graphical model for inferring dynamic gene regulatory networks from genomic high-throughput data. The model allows including dynamic-related equality constraints on the precision matrix as well as imposing sparsity constraints in the estimation procedure. I will discuss model selection and present an application on a high-resolution 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 sglasso, freely available from CRAN.


The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.
Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons