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Ronald Westra, Goele Hollanders, Ralf Peeters, and Karl Tuyls. Piecewise Linear Modeling of Gene-Protein Interaction Networks. In Proceedings of the Knowledge Discovery and Emergent Complexity workshop, May 10th, Ghent, Belgium, 2006.
In this study we will focus on piece-wise linear state space modelsfor gene-protein interaction networks. We will follow the dynamical systems approachwith special interest for partitioned state spaces. From the observation thatthe dynamics in natural systems tends to punctuated equilibria, we will focus onpiecewise linear models and sparse and hierarchic interactions, as for instance describedby Glass, Kauffman, and de Jong. Next, the paper is concerned with theidentification (a.k.a. reverse engineering and reconstruction) of dynamic geneticnetworks from microarray data. We will describe exact and robust methods forcomputing the interaction matrix in the special case of piecewise linear modelswith sparse and hierarchic interactions from partial observations. Finally, we willanalyze and evaluate this approach with regard to its performance and robustnesstowards intrinsic and extrinsic noise
@INPROCEEDINGS{Westrakdecb06,
author = {Ronald Westra and Goele Hollanders and Ralf Peeters and Karl Tuyls},
title = {Piecewise Linear Modeling of Gene-Protein Interaction Networks},
booktitle = {Proceedings of the Knowledge Discovery and Emergent Complexity workshop},
year = {2006},
address = {May 10th, Ghent, Belgium},
abstract = {In this study we will focus on piece-wise 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 (a.k.a. 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},
bib2html_pubtype = {Refereed Workshop},
bib2html_rescat = {Bioinformatics},
owner = {K.Tuyls},
timestamp = {2006.11.23},
}
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