Elucidating the structure of genetic regulatory networks: A study of a second order dynamical model on artificial data

ESANN 2006 Proceedings - European Symposium on Artificial Neural Networks

Volumn , Issue , 2006, Pages 569-574

  Quach, Minh ^a   Geurts, Pierre ^a,b   D'Alché Buc, Florence ^a  

^a UNIVERSITY OF EVRY   (France)

^b UNIVERSITY OF LIÈGE   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; NEURAL NETWORKS; STATE SPACE METHODS;

ARTIFICIAL DATA; DYNAMICAL MODEL; GENETIC REGULATORY NETWORKS; NETWORK STRUCTURES; PROBLEM PARAMETERS; REGULATORY NETWORK; SPECTRAL CLUSTERING; STATE - SPACE MODELS;

GENE EXPRESSION;

EID: 85069778578     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. P. D'haeseleer, S. Liang, and R. Somogyi. Genetic network inference: From co-expression clustering to reverse engineering. BioInformatics, 16(8):707-726, 2000.
2. S. Kim, S. Imoto, and S. Miyano. Dynamic bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data. In Proc. of CMSB 2003, pages 104-113, 2003.
3. A. Regev I. Nachman and N. Friedman. Inferring quantitative models of regulatory networks from expression data. Bioinformatics, Vol. 20 Suppl. 1:i248-i256, 2004.
4. B-E. Perrin, L. Ralaivola, A. Mazurie, S. Bottani, J. Mallet, and F. D'Alché-Buc. Gene networks inference using dynamic bayesian networks. Bioinformatics, Vol. 19 Suppl. 2:i138-i148, 2003.
5. F. d'Alché Buc, P.-J. Lahaye, B.-E. Perrin, L. Ralaivola, T. Vujasinovic, A. Mazurie, and S. Bottani. Bioinformatics Using Computational Intelligence Paradigms, chapter A dynamical system based on inertia principle for gene regulatory network modeling, pages 93-118. Springer, 2005.