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Abstract:
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Reverse engineering the genetic networks that describe the regulatory interaction among genes is one of the major challenges of modern biology. In this paper, we propose forward network identification regression (FNIR) and experiment planning of gene overexpression in gene array experiments using D-optimal designs. In our approach, the gene network is inferred by applying FNIR to the expression data obtained by perturbing the expression of a few carefully chosen genes per experiment. The proposed methods are compared with alternatives using simulation and data sets motivated by the SOS pathway for Escherichia coli bacteria. Findings include that D-optimal experimental planning can likely improve the sensitivity, specificity, and efficiency. Topics for further research are suggested including numerically stable analysis methods, improved diagnostics, and sequential methods.
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