Evidence map›Paper›PMID 21850044›Full record

ReviewNature reviews. Genetics2011

Understanding the transcriptome through RNA structure.

Yue Wan, Michael Kertesz, Robert C Spitale, Eran Segal, Howard Y Chang

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 247 papers.

0numbers the graph read from it
0cells of the map it votes in
247citing 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

247 citing papers in PubMed.

  1. Article
  2. Article
  3. A long non-coding RNA,mSphere · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. A long non-coding RNA,bioRxiv : the preprint server for biology · 2026
    Article
  8. bioRxiv : the preprint server for biology · 2026
    Article
  9. RNA Structure Analysis by Chemical Probing with DMS and CMCT.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review

187 more citing papers are in PubMed but not listed here.

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

5 authors.

Yue WanHoward Hughes Medical Institute and Program in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA.
Michael Kertesz
Robert C Spitale
Eran Segal
Howard Y Chang

Funding

Structural Motifs in RNAR01HG004361 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2007 to 2018
$4.7M
Howard Hughes Medical InstituteNHGRI NIH HHS R01 HG004361NHGRI NIH HHS R01-HG004361
6 · The paper itself

Abstract

RNA structure is crucial for gene regulation and function. In the past, transcriptomes have largely been parsed by primary sequences and expression levels, but it is now becoming feasible to annotate and compare transcriptomes based on RNA structure. In addition to computational prediction methods, the recent advent of experimental techniques to probe RNA structure by high-throughput sequencing has enabled genome-wide measurements of RNA structure and has provided the first picture of the structural organization of a eukaryotic transcriptome - the 'RNA structurome'. With additional advances in method refinement and interpretation, structural views of the transcriptome should help to identify and validate regulatory RNA motifs that are involved in diverse cellular processes and thereby increase understanding of RNA function.

Indexed as

AnimalsComputational BiologyGene Expression ProfilingGene Expression RegulationGenomeHumansMammalsMicroRNAsNucleic Acid ConformationRiboswitchRNARNA-Binding ProteinsSequence Analysis, RNAThermodynamicsMicroRNAsRiboswitchRNARNA-Binding Proteins

Identifiers

PMID21850044
PMCPMC3858389

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

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.