Computational Approaches to RNAi and Gene Silencing

The discovery of small regulatory RNAs in the past few years has deeply changed the RNA molecular biology, revealing more complex pathways involved in the regulation of gene expression and in the defense of the genome against exogenous nucleic acids. These small RNA molecules play a crucial role in many physiological processes. Aberrations in their sequences and expression patterns are often related to the development of malignant diseases. The underlying biological mechanisms are known as gene silencing and RNA interference (RNAi). This discovery not only changes our conception of gene expression regulation but, at the same time, opens new frontiers for the development of therapeutic approaches, more specific and less toxic, especially against all those diseases which are still resistant to traditional treatment. Computational techniques constitute an essential tool in the study of these complex systems. Many existing bioinformatics methods and newly developed approaches have been used to analyze and classify RNAi data and more sophisticated tools are needed to allow a better understanding of the small RNAs biogenesis, processing and functions. In this essay we will review the basics of gene expression regulation by small RNA molecules and discuss the main computational issues in RNAi research, focusing on the most popular algorithms and addressing the open challenges.