
Abstract Motivation: Short interfering RNAs (siRNAs) can be used to suppress gene expression and possess many potential applications in therapy, but how to design an effective siRNA is still not clear. Based on the MPI (Max-Planck-Institute) basic principles, a number of siRNA design tools have been developed recently. The set of candidates reported by these tools is usually large and often contains ineffective siRNAs. In view of this, we initiate the study of filtering ineffective siRNAs. Results: The contribution of this paper is 2-fold. First, we propose a fair scheme to compare existing design tools based on real data in the literature. Second, 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. Availability: The siRNA design software tool can be found in the website http://www.cs.hku.hk/~sirna/ Contact: smyiu@cs.hku.hk
Models, Molecular, Artificial intelligence, Sequence analysis, rna, Molecular Sequence Data, Computer-aided design, Models, Artificial Intelligence, rna, molecular, RNA, Small Interfering, Base Sequence, Sequence Analysis, RNA, Sequence analysis, 006, Benchmarking, Models, Chemical, Computer-Aided Design, Genetic Engineering, Sequence Alignment, Models, molecular, Algorithms, Software
Models, Molecular, Artificial intelligence, Sequence analysis, rna, Molecular Sequence Data, Computer-aided design, Models, Artificial Intelligence, rna, molecular, RNA, Small Interfering, Base Sequence, Sequence Analysis, RNA, Sequence analysis, 006, Benchmarking, Models, Chemical, Computer-Aided Design, Genetic Engineering, Sequence Alignment, Models, molecular, Algorithms, Software
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