Evaluation of Time Series Microarray Data for Dynamic Gene Regulatory Network Inference

Microarray data are primarily used by gene regulatory network inference algorithms. We used dynamic artificial gene regulatory networks to evaluate the adequacy of time course microarray data to support the inference process. We evaluated the effect of different ways that genes can be triggered on the performance of an inference algorithm. We evaluated the effect of sparseness of a network on the inference performance. Finally we evaluated the effect of noise in microarray data on the inference process.