Making large-scale support vector machine learning practical
Advances in kernel methods
OptiRNai, a Web-based Program to Select siRNA Sequences
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
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Short interfering RNAs (siRNAs) can be used to suppress gene expression and have many potential applications in therapy, yet how to design an effective siRNA is still not clear. Based on the MPI basic principles (Tuschl, Elbashir, Harborth & Weber 2003), a number of siRNA design tools have been developed in the past two years. The set of candidates output by these tools is usually large and often contains some ineffective siRNAs. In view of this, we initiate the study of filtering ineffective siRNAs. The contribution of this paper is two-fold. Firstly, we propose a fair scheme to compare existing design tools based on real data in the literature. Secondly, we attempt to improve the MPI principles and existing tools by an algorithm that can filter ineffective siRNAs. The algorithm is based on some new observations on the secondary structure, which we have verified by AI techniques (decision trees and support vector machines). We have tested our algorithm together with the MPI principles and the existing tools. The results show that our filtering algorithm is effective.