Evidence map›Paper›PMID 17129386›Full record

ArticleBMC bioinformatics2006

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness.

Wuming Gong, Yongliang Ren, Qiqi Xu, Yejun Wang, Dong Lin, Haiyan Zhou, Tongbin Li

Abstract read
In one paragraph

Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. siRNA Design and GalNAc-Empowered Hepatic Targeted Delivery.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
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  4. Computational design of artificial RNA molecules for gene regulation.Methods in molecular biology (Clifton, N.J.) · 2015
    Article
  5. Article
  6. Design of siRNA Therapeutics from the Molecular Scale.Pharmaceuticals (Basel, Switzerland) · 2013
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Wuming GongDepartment of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>
Yongliang Ren
Qiqi Xu
Yejun Wang
Dong Lin
Haiyan Zhou
Tongbin Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundShort interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins.

resultsUsing a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs).

conclusionThe availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies.

Indexed as

AlgorithmsDatabases, Nucleic AcidDrug DesignRNA InterferenceBase SequenceMolecular Sequence DataRNA, Small InterferingSequence Analysis, RNAStructure-Activity RelationshipRNA, Small Interfering

Identifiers

PMID17129386
PMCPMC1698580

What OpenQuestion holds

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Registered trials

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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.