Evidence map›Paper›PMID 21127008›Full record

ReviewBriefings in functional genomics2010

Deciphering the role of RNA-binding proteins in the post-transcriptional control of gene expression.

Shivendra Kishore, Sandra Luber, Mihaela Zavolan

Open access · bronzeAbstract readReview
In one paragraph

Review in Briefings in functional genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
96citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% of its field
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

96 citing papers in PubMed, 1 synthesis or guideline pooled it, 193 citations in OpenAlex.

  1. Pooled it
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  11. Coding relationship links RNA G-quadruplexes and protein RGG motifs in RNA-binding protein autoregulation.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  20. Modulation of Virulence Factors duringPathogens (Basel, Switzerland) · 2022
    Review

36 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

3 authors at 1 institution in 1 country.

Shivendra KishoreUniversity of Basel, Switzerland.
Sandra Luber
Mihaela Zavolan
University of Basel · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Eukaryotic cells express a large variety of ribonucleic acid-(RNA)-binding proteins (RBPs) with diverse affinity and specificity towards target RNAs that play a crucial role in almost every aspect of RNA metabolism. In addition, specific domains in RBPs impart catalytic activity or mediate protein-protein interactions, making RBPs versatile regulators of gene expression. In this review, we elaborate on recent experimental and computational approaches that have increased our understanding of RNA-protein interactions and their role in cellular function. We review aspects of gene expression that are modulated post-transcriptionally by RBPs, namely the stability of polymerase II-derived mRNA transcripts and their rate of translation into proteins. We further highlight the extensive regulatory networks of RBPs that implement a combinatorial control of gene expression. Taking cues from the recent development in the field, we argue that understanding spatio-temporal RNA-protein association on a transcriptome level will provide invaluable and unexpected insights into the regulatory codes that define growth, differentiation and disease.

Indexed as

RNA Processing, Post-TranscriptionalAnimalsComputational BiologyGene Expression ProfilingHumansRNA-Binding ProteinsRNA, MessengerRNA-Binding ProteinsRNA, Messenger

Identifiers

PMID21127008
PMCPMC3080770
OpenAlexW2148542126

What OpenQuestion holds

Textmetadata
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.