Quantitative Estimation of siRNAs Gene Silencing Capability by Random Forest Regression Model

Although the observations concerning the factors which influence the siRNA efficacy give clues to the mechanism of RNAi, the quantitative prediction of the siRNA efficacy is still a challenge task. In this paper, we introduced a novel non-linear regression method: random forest regression (RFR), to quantitatively estimate siRNAs efficacy values. Compared with an alternative machine learning regression algorithm, support vector machine regression (SVR) and four other score-based algorithms (Reynolds et al. (2004), Ui-Tei et al. (2004), Hsieh et al. (2004), Amarzguioui et al. (2004)) our RFR model achieved the best performance of all.