Designer of Small Interfering RNA
DSIR: Supplementary informations
Vert JP, Foveau N, Lajaunie C, Vandenbrouck Y. An accurate and interpretable model for siRNA efficacy prediction.BMC Bioinformatics. 2006 Nov 30;7(1):520.
Please cite this paper, if you use DSIR
We built a linear model on a set of siRNA provided by Huesken et al. (Nat. Biotechnol., 23(8):995-1001, 2005. Trained on the training set of 2182 sequences below, it reaches a Pearson correlation coefficient of 0.67 on the test set of 249 siRNA available below. The model implemented on this server has been trained on the training and test set pooled together, therefore its weights (available below) differ slightly from the weights published in the reference article.
- Weights of the linear model (21 nt)
- Weights of the linear model (19 nt)
- Training set of 2182 siRNA sequences
- Test set of 249 sequences
The set of siRNA experimentally validated for computational model assessment published in Filhol O, Ciais D, Lajaunie C, Charbonnier P, Foveau N, et al. (2012) DSIR: Assessing the Design of Highly Potent siRNA by Testing a Set of Cancer-Relevant Target Genes. PLoS ONE 7(10): e48057.
- Feb 21, 2012 : add a new siRNA dataset
- Jul 28, 2009 : corrected score with penalties deduced from target features is added
- Jan 16, 2009 : seed frequencies computing against 3'UTR databanks is added
- Oct 10, 2008 : filters on polynucleotides tracts and immunostimulatory motifs are added.
- Dec 12, 2007 : exact similarity search algorithm for potential off-target detection is added.
- Jul 6, 2007 : the prediction of 19nt siRNA is added.
- Nov 30, 2006 : DSIR is publicly available.