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Microarray studies are capable of providing data for temporal gene expression patterns of thousands of genes simultaneously, comprising rich but cryptic information about transcriptional control. However available methods are still not adequate in extraction of useful information about transcriptional regulation from these data. This study presents a(More)
Inference of gene expression networks has become one of the primary challenges in computational biology. Analysis of microarray experiments using appropriate mathematical models can reveal interactions among protein regulators and target genes. This paper presents a combined approach to the inference of gene expression networks from time series(More)
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