Understanding the regulation of gene expression is critical to many areas of biology while control via RNAs has found considerable interest as a tool for scientific discovery and potential therapeutic applications. For example whole genome RNA interference (RNAi) screens and whole proteome scans provide views of how the entire transcriptome or proteome responds to biological, chemical or environmental perturbations of a gene's activity. Small RNA (sRNA) or MicroRNA (miRNA) are known to regulate pathways and bind mRNA, while the function of miRNAs discovered in experimental studies is often unknown. In both cases, RNAi and miRNA require labor intensive studies to tease out their functions within gene networks. Available software to analyze relationships is currently an ad hoc and often a manual process that can take up to several hours to analyze a single candidate RNAi or miRNA. With experiments frequently highlighting tens to hundreds of candidates this represents a considerable bottleneck. We suggest there is a gap in miRNA and RNAi research caused by inadequate current software that could be improved. For example a new software application could be created that provides interactive, comprehensive target analysis that leverages past datasets to lead to statistically stronger analyses.