Christian Spieth, Felix Streichert, Nora Speer, and Andreas Zell
A Memetic Inference Method for Gene Regulatory Networks Based on S-Systems
Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2004)
Abstract
In this paper we address the problem of finding gene regulatory
networks from experimental DNA microarray data. As underlying
mathematical model we used S-Systems, a quantitative model, which
recently has found increased attention in the literature. Due to
the complexity of the inference problem some researchers suggested
Evolutionary Algorithms for this purpose. We introduce
enhancements to this optimization process to infer the parameters
of sparsely connected non-linear systems given by the observed
data more reliably and precisely. Due to the limited number of
available data the inferring problem is under-determined and
ambiguous. Further on, the problem often is multi-modal and
therefore appropriate optimization strategies become necessary. In
this paper we propose a new method, which evolves the topology as
well as the parameters of the mathematical model to find the
correct network. This method is compared to standard algorithms
found in the literature.
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BibTeX
@INPROCEEDINGS{spieth04memetic,
author = {Christian Spieth and Felix Streichert and Nora Speer and Andreas Zell},
title = {A Memetic Inference Method for Gene Regulatory Networks Based on S-Systems},
booktitle = {Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2004)},
year = {2004},
pages = {152-157},
}