PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Elucidating the structure of genetic regulatory networks: a study of a second order dynamical model on artificial data
Minh Quach, Pierre Geurts and Florence d'Alché-Buc
In: ESANN, 26-28 April 2006, Bruges, Belgium.


Learning regulatory networks from time-series of gene expression is a challenging task. We propose to use synthetic data to analyze the ability of a state-space model to retrieve the network structure while varying a number of relevant problem parameters. ROC curves together with new tools such as spectral clustering of local solutions found by EM are used to analyze these results and provide relevant insights.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:2733
Deposited By:Minh Quach
Deposited On:22 November 2006