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RNA interference (RNAi) is a recently developed reverse genetic tool to knockdown expression of specific genes in eukaryotes. Successful implementation of this technology requires the design of double stranded RNAs identical to specific regions of the target gene. However, not every possible small interfering RNA (siRNA) is able to reduce target gene expression. Recently, Elbashir et al has established empirical criteria for siRNA sequence selection that significantly improved the success rate for RNAi attempts. We have developed OptiRNAi, a computational tool, which uses the Elbashir et al criteria to predict appropriate sequences for siRNA production. The output of the program provides researchers with a number of potential siRNA targets, a score that reflects how well the sequence fulfills the empirical criteria, and the location of the target sequence in the input. Specificity of these siRNAs for the target of interest can then be assessed by the investigator using the embedded Blast server optimized for RNAi design. Thus, OptiRNAi is a labor saving tool for RNAi design using criteria that are more stringent than other available tools.