Efficient siRNA selection using hybridization thermodynamics.

@article{citeulike:2333412, abstract = {Small interfering RNA (siRNA) are widely used to infer gene function. Here, insights in the equilibrium of siRNA-target hybridization are used for selection of efficient siRNA. The accessibilities of siRNA and target mRNA for hybridization, as measured by folding free energy change, are shown to be significantly correlated with efficacy. For this study, a partition function calculation that considers all possible secondary structures is used to predict target site accessibility; a significant improvement over calculations that consider only the predicted lowest free energy structure or a set of low free energy structures. The predicted thermodynamic features, in addition to siRNA sequence features, are used as input for a support vector machine that selects functional siRNA. The method works well for predicting efficient siRNA (efficacy >70\%) in a large siRNA data set from Novartis. The positive predictive value (percentage of sites predicted to be efficient for silencing that are) is as high as 87.6\%. The sensitivity and specificity are 22.7 and 96.5\%, respectively. When tested on data from different sources, the positive predictive value increased 8.1\% by adding equilibrium terms to 25 local sequence features. Prediction of hybridization affinity using partition functions is now available in the RNAstructure software package.}, address = {Department of Biochemistry \& Biophysics and Department of Biostatistics \& Computational Biology, University of Rochester Medical Center, 601 Elmwood Avenue, Box 712, Rochester, NY 14642, USA.}, author = {Lu, Z. J. and Mathews, D. H. }, citeulike-article-id = {2333412}, issn = {1362-4962}, journal = {Nucleic Acids Res}, month = {February}, number = {2}, pages = {640--647}, posted-at = {2008-05-13 09:16:37}, priority = {2}, title = {Efficient siRNA selection using hybridization thermodynamics.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/18073195}, volume = {36}, year = {2008} }

TY - JOUR ID - citeulike:2333412 L3 - citeulike-article-id:2333412 TI - Efficient siRNA selection using hybridization thermodynamics. JF - Nucleic Acids Res VL - 36 IS - 2 SP - 640 EP - 647 AD - Department of Biochemistry & Biophysics and Department of Biostatistics & Computational Biology, University of Rochester Medical Center, 601 Elmwood Avenue, Box 712, Rochester, NY 14642, USA. SN - 1362-4962 N2 - Small interfering RNA (siRNA) are widely used to infer gene function. Here, insights in the equilibrium of siRNA-target hybridization are used for selection of efficient siRNA. The accessibilities of siRNA and target mRNA for hybridization, as measured by folding free energy change, are shown to be significantly correlated with efficacy. For this study, a partition function calculation that considers all possible secondary structures is used to predict target site accessibility; a significant improvement over calculations that consider only the predicted lowest free energy structure or a set of low free energy structures. The predicted thermodynamic features, in addition to siRNA sequence features, are used as input for a support vector machine that selects functional siRNA. The method works well for predicting efficient siRNA (efficacy >70%) in a large siRNA data set from Novartis. The positive predictive value (percentage of sites predicted to be efficient for silencing that are) is as high as 87.6%. The sensitivity and specificity are 22.7 and 96.5%, respectively. When tested on data from different sources, the positive predictive value increased 8.1% by adding equilibrium terms to 25 local sequence features. Prediction of hybridization affinity using partition functions is now available in the RNAstructure software package. AU - Lu, ZJ AU - Mathews, DH PY - 2008/02// UR - http://view.ncbi.nlm.nih.gov/pubmed/18073195 ER -