ArticleNucleic acids research2007
More complete gene silencing by fewer siRNAs: transparent optimized design and biophysical signature.
Article in Nucleic acids research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 64 citations in OpenAlex.
- From rules to foundation models: a comprehensive review of machine learning approaches for siRNA design.NAR genomics and bioinformatics · 2026Review
- OligoFormer: an accurate and robust prediction method for siRNA design.Bioinformatics (Oxford, England) · 2024Article
- RNAi-Mediated Silencing in the Insect Cell-Baculovirus Expression System.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Cheminformatics Modeling of Gene Silencing for Both Natural and Chemically Modified siRNAs.Molecules (Basel, Switzerland) · 2022Article
- siRNA Design and GalNAc-Empowered Hepatic Targeted Delivery.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Designing Tyrosinase siRNAs by Multiple Prediction Algorithms and Evaluation of Their Anti-Melanogenic Effects.Biomolecules & therapeutics · 2018Article
- In Silico Design and Experimental Validation of siRNAs Targeting Conserved Regions of Multiple Hepatitis C Virus Genotypes.PloS one · 2016Article
- Effect of siRNA pre-Exposure on Subsequent Response to siRNA Therapy.Pharmaceutical research · 2015Article
- Improved asymmetry prediction for short interfering RNAs.The FEBS journal · 2014Article
- Design of siRNA Therapeutics from the Molecular Scale.Pharmaceuticals (Basel, Switzerland) · 2013Article
- Mini-clusters with mean probabilities for identifying effective siRNAs.BMC research notes · 2012Article
- siRNA Design Software for a Target Gene-Specific RNA Interference.Frontiers in genetics · 2012Article
- Development of Therapeutic-Grade Small Interfering RNAs by Chemical Engineering.Frontiers in genetics · 2012Article
- Optimized models for design of efficient miR30-based shRNAs.Frontiers in genetics · 2012Article
- MysiRNA-designer: a workflow for efficient siRNA design.PloS one · 2011Article
- Predicting siRNA potency with random forests and support vector machines.BMC genomics · 2010Article
- RNA interference inhibits hepatitis E virus mRNA accumulation and protein synthesis in vitro.Veterinary microbiology · 2010Article
- Article
- Selection of hyperfunctional siRNAs with improved potency and specificity.Nucleic acids research · 2009Article
- Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Highly accurate knockdown functional analyses based on RNA interference (RNAi) require the possible most complete hydrolysis of the targeted mRNA while avoiding the degradation of untargeted genes (off-target effects). This in turn requires significant improvements to target selection for two reasons. First, the average silencing activity of randomly selected siRNAs is as low as 62%. Second, applying more than five different siRNAs may lead to saturation of the RNA-induced silencing complex (RISC) and to the degradation of untargeted genes. Therefore, selecting a small number of highly active siRNAs is critical for maximizing knockdown and minimizing off-target effects. To satisfy these needs, a publicly available and transparent machine learning tool is presented that ranks all possible siRNAs for each targeted gene. Support vector machines (SVMs) with polynomial kernels and constrained optimization models select and utilize the most predictive effective combinations from 572 sequence, thermodynamic, accessibility and self-hairpin features over 2200 published siRNAs. This tool reaches an accuracy of 92.3% in cross-validation experiments. We fully present the underlying biophysical signature that involves free energy, accessibility and dinucleotide characteristics. We show that while complete silencing is possible at certain structured target sites, accessibility information improves the prediction of the 90% active siRNA target sites. Fast siRNA activity predictions can be performed on our web server at http://optirna.unl.edu/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.