Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/7972
Title: The Identification of Dynamic Gene-Protein Networks
Authors: WESTRA, Ronald 
HOLLANDERS, Goele 
BEX, Geert Jan 
GYSSENS, Marc 
TUYLS, Karl 
Issue Date: 2007
Publisher: Springer-Verlag
Source: Knowledge Discovery and Emergent Complexity in Bioinformatics, First International Workshop, KDECB 2006, Ghent, Belgium, May 2006, Revised Selected Papers. p. 157-170
Series/Report: LECTURE NOTES IN COMPUTER SCIENCE
Series/Report no.: 4366
Abstract: In this study we will focus on piecewise linear state space models for gene-protein interaction networks. We will follow the dynamical systems approach with special interest for partitioned state spaces. From the observation that the dynamics in natural systems tends to punctuated equilibria, we will focus on piecewise linear models and sparse and hierarchic interactions, as, for instance, described by Glass, Kauffman, and de Jong. Next, the paper is concerned with the identification (also known as reverse engineering and reconstruction) of dynamic genetic networks from microarray data. We will describe exact and robust methods for computing the interaction matrix in the special case of piecewise linear models with sparse and hierarchic interactions from partial observations. Finally, we will analyze and evaluate this approach with regard to its performance and robustness towards intrinsic and extrinsic noise.
Keywords: piecewise linear model, robust identification, hierarchical networks, microarrays
Document URI: http://hdl.handle.net/1942/7972
ISBN: 978-3-540-71036-3
DOI: 10.1007/978-3-540-71037-0_11
Category: A2
Type: Journal Contribution
Appears in Collections:Research publications

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