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Antisense techniques are powerful tools for the inhibition of gene expression in the target discovery and validation phases of pharmaceutical research. In particular, RNA interference has become a method of choice to investigate the roles of putative target genes in models of disease states. This technique is technically demanding, particularly when it is applied in complex experiments such as high-throughput genome analysis or in animal models of disease. We describe here two areas of current research in our group, dedicated to advancing these techniques: the use of neural networks to predict the biological activity of short interfering RNAs, and the application of siRNAs in animal models of disease.