ArticlePloS one2011
siPRED: predicting siRNA efficacy using various characteristic methods.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- RNAi-based therapeutics targeting the F gene in human metapneumovirus: An in-silico approach.Journal, genetic engineering & biotechnology · 2026Article
- Strategic Computational Design of siRNA Molecules Targeting Structural Genes of SARS-CoV-2.Applied biochemistry and biotechnology · 2026Article
- Designing siRNAs against non-structural genes of all serotypes of Dengue virus using RNAi technology - A computational investigation.Journal, genetic engineering & biotechnology · 2025Article
- In Silico and In Vitro development of novel small interfering RNAs (siRNAs) to inhibit SARS-CoV-2.Computational and structural biotechnology journal · 2025Article
- siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis.Briefings in bioinformatics · 2024Article
- Article
- Asymmetric trichotomous partitioning overcomes dataset limitations in building machine learning models for predicting siRNA efficacy.Molecular therapy. Nucleic acids · 2023Article
- Multiple integrations of a sense transgene, including a tandem inverted repeat confer stable RNA-silencing mediated virus resistance under different abiotic and biotic conditions.Transgenic research · 2023Article
- Constructing the boundary between potent and ineffective siRNAs by MG-algorithm with C-features.BMC bioinformatics · 2022Article
- In Silico Prediction and Selection of Target Sequences in the SARS-CoV-2 RNA Genome for an Antiviral Attack.Viruses · 2022Article
- Targeting genomic SARS-CoV-2 RNA with siRNAs allows efficient inhibition of viral replication and spread.Nucleic acids research · 2022Article
- From genomes to molecular dynamics - A bottom up approach in extrication of SARS CoV-2 main protease inhibitors.Computational toxicology (Amsterdam, Netherlands) · 2021Article
- Introducing an In Vitro Liver Stability Assay Capable of Predicting the In Vivo Pharmacodynamic Efficacy of siRNAs for IVIVC.Molecular therapy. Nucleic acids · 2020Article
- Functional features defining the efficacy of cholesterol-conjugated, self-deliverable, chemically modified siRNAs.Nucleic acids research · 2018Article
- ASPsiRNA: A Resource of ASP-siRNAs Having Therapeutic Potential for Human Genetic Disorders and Algorithm for Prediction of Their Inhibitory Efficacy.G3 (Bethesda, Md.) · 2017Article
- Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level.Scientific reports · 2017Article
- SMEpred workbench: A web server for predicting efficacy of chemicallymodified siRNAs.RNA biology · 2016Article
- VIRsiRNApred: a web server for predicting inhibition efficacy of siRNAs targeting human viruses.Journal of translational medicine · 2013Article
- Antiviral Stratagems Against HIV-1 Using RNA Interference (RNAi) Technology.Evolutionary bioinformatics online · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small interfering RNA (siRNA) has been used widely to induce gene silencing in cells. To predict the efficacy of an siRNA with respect to inhibition of its target mRNA, we developed a two layer system, siPRED, which is based on various characteristic methods in the first layer and fusion mechanisms in the second layer. Characteristic methods were constructed by support vector regression from three categories of characteristics, namely sequence, features, and rules. Fusion mechanisms considered combinations of characteristic methods in different categories and were implemented by support vector regression and neural networks to yield integrated methods. In siPRED, the prediction of siRNA efficacy through integrated methods was better than through any method that utilized only a single method. Moreover, the weighting of each characteristic method in the context of integrated methods was established by genetic algorithms so that the effect of each characteristic method could be revealed. Using a validation dataset, siPRED performed better than other predictive systems that used the scoring method, neural networks, or linear regression. Finally, siPRED can be improved to achieve a correlation coefficient of 0.777 when the threshold of the whole stacking energy is ≥-34.6 kcal/mol. siPRED is freely available on the web at http://predictor.nchu.edu.tw/siPRED.
Indexed as
Identifiers
What OpenQuestion holds
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.