Guidelines for the selection of highly effective siRNA sequences for mammalian and chick RNA interference.

By Kumiko Ui-Tei, Yuki Naito, F. Takahashi, T. Haraguchi, H. Ohki-Hamazaki, Aya Juni, R. Ueda, K. Saigo. Nucleic Acids Research, 2004

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Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study (2010, background): “Further investigations include the study of the RNAi mechanism itself as well as characteristics of siRNAs with either high or low silencing capacity [10-16].”
Design of a genome-wide siRNA library using an artificial neural network (2005, background): “Finally, strong internal structures, an absence of G/C stretches and a prevalence of certain nucleotides at positions 4, 7, 9, 14 and at the 3 ¢ -end are also characteristic of active siRNAs 8–10 .”
Reciprocal Transcriptional Regulation of Pou5f1 and Sox2 via the Oct4/Sox2 Complex in Embryonic Stem Cells (2005, methodology): “These regions were selected based on their Reynolds scores and Ui-Tei class values (37, 48).”
Synthetic dsRNA Dicer substrates enhance RNAi potency and efficacy (2005, methodology): “, necessitating complex design algorithms to predict effective site”
Perspective: machines for RNAi. (2005, background): “2003; Gong and Ferrell 2004), and we implore readers to explore these “design rules” before synthesizing siRNAs to reduce expression of a favorite gene (Khvorova et al. 2003; Amarzguioui and Prydz 2004; Hohjoh 2004; Naito et al. 2004; Reynolds et al. 2004; Ui-Tei et al. 2004; Yiu et al. 2005).”