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Optimizing Topology and Parameters of Gene Regulatory Network Models from Time-Series Experiments
[chapter]
2004
Lecture Notes in Computer Science
In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. Different approaches to infer the dependencies of gene regulatory networks by identifying parameters of mathematical models like complex S-systems or simple Random Boolean Networks can be found in literature. Due to the complexity of the inference problem some researchers suggested Evolutionary Algorithms for this purpose. We introduce enhancements to the Evolutionary Algorithm
doi:10.1007/978-3-540-24854-5_46
fatcat:swc5bk3zzbax7p53m7lsukskti