Abstracts
- 09/01/2012 - V. A. Huynh-Thu
- 09/01/2012 - R. Küffner
- 09/01/2012 - C. Ambroise
- 16/09/2011 - M. Bunster
- 27/04/2011 - P. Meyer
- 06/04/2011 - D. Débois
- 30/03/2011 - J. Wouters
- 28/01/2011 - J.-C. Lambert
- 13/12/2010 - J. Giard
- 17/11/2010 - B. Charloteaux
- 12/05/2010 - P. Soumillion
- 30/04/2010 - J.-P. Vert
- 14/04/2010 - X. Tordoir
- 24/03/2010 - J.C. Voegel
- 17/03/2010 - A. Turtoi
- 24/02/2010 - L. Palmeira
- 27/01/2010 - D. Devos
- 09/12/2009 - F. Heuze
- 25/11/2009 - L. Geris
- 19/11/2009 - V. Gabelica
- 14/10/2009 - G. Zocchi
- 30/09/2009 - K. Van Steen
- 12/06/2009 - D. Gianola
- 05/06/2009 - F. J. Theis
- 02/06/2009 - M. Babu
- 07/05/2009 - J. Eyzaguirre
- 22/04/2009 - E. Bullinger
- 08/04/2009 - F. Francis
- 04/03/2009 - Kick-off
Cancer gene identification with trees and walks
Alexandre Irrthum (GIGA Systems and Modeling Unit)
Date and place: Wednesday December, 1st 12:45 pm at 1.75 (B6c)
In this talk, we will present work in progress that bears upon the identification of candidate cancer genes based on the concept of guilt by association. In this approach, a genome-wide network of associations between genes is obtained experimentally or inferred computationally, and genes close to known disease genes in the network are identified as candidates. We will show how GENIE3, a new algorithm based on ensembles of regression trees developed in our group, is suited to the inference of a network relevant to cancer biology from expression data. We will then go on to show how new candidate genes are identified by propagation of carefully chosen annotations in the network with random walks. The described approach is algorithmically simple, yet powerful, allowing the combination of multiple biological hints. Some examples and extensions will be also discussed.