Reference : Looking for applications of mixtures of Markov trees in bioinformatics
Scientific conferences in universities or research centers : Scientific conference in universities or research centers
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/87686
Looking for applications of mixtures of Markov trees in bioinformatics
English
Schnitzler, François mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
21-Mar-2011
A0
National
BioMAGNet Annual Meeting 2011
Bruxelles
Belgium
[en] bayesian networks ; mixture of trees ; Markov trees
[en] Probabilistic graphical models (PGM) efficiently encode a probability distribution on a large set of
variables. While they have already had several successful applications in biology, their poor scaling in terms
of the number of variables may make them unfit to tackle problems of increasing size. Mixtures of trees
however scale well by design. Experiments on synthetic data have shown the interest of our new learning
methods for this model, and we now wish to apply them to relevant problems in bioinformatics.
Systèmes et Modélisation
Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA ; Biomagnet IUAP network of the Belgian Science Policy Office ; Pascal2 network of excellence of the EC
Researchers
http://hdl.handle.net/2268/87686

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