Selecting effective siRNA sequences based on the self-organizing map and statistical techniques

Short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells but varies markedly in its gene-silencing efficacy. Although many design rules/guidelines for effective siRNAs based on various criteria have been reported recently, there are only a few consistencies among them. This makes it difficult to select effective siRNA sequences in mammalian genes. Here, we propose a new method for selecting effective siRNA target sequences on the basis of the self-organizing map (SOM) technique and statistical significance analyses for a large number of effective siRNAs. In the proposed method, the score is defined as a gene degradation measure. The effectiveness for the proposed method was confirmed by evaluating effective and ineffective siRNAs for recently reported genes (12 genes, 172 siRNA sequences) and comparing with other reported scoring methods. The size (value) of this score is closely correlated with the degree of gene degradation, and the score can easily be used for selecting high-potential siRNA candidates. The evaluation results indicate that the proposed method would be useful for many other genes. It will therefore be useful for selecting siRNA sequences in mammalian genes.