Evidence map›Paper›PMID 24951655›Full record

ReviewBriefings in functional genomics2015

Biochemical and bioinformatic methods for elucidating the role of RNA-protein interactions in posttranscriptional regulation.

Andreas Kloetgen, Philipp C Münch, Arndt Borkhardt, Jessica I Hoell, Alice C McHardy

Erratum issuedAbstract readReview
In one paragraph

Review in Briefings in functional genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Revealing protein-lncRNA interaction.Briefings in bioinformatics · 2016
    Review
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Andreas Kloetgen
Philipp C Münch
Arndt Borkhardt
Jessica I Hoell
Alice C McHardy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our understanding of transcriptional gene regulation has dramatically increased over the past decades, and many regulators of gene expression, such as transcription factors, have been analyzed extensively. Additionally, in recent years, deeper insights into the physiological roles of RNA have been obtained. More precisely, splicing, polyadenylation, various modifications, localization and the translation of messenger RNAs (mRNAs) are regulated by their interaction with RNA-binding proteins (RBPs). New technologies now enable the analysis of this regulation at different levels. A technique known as ultraviolet (UV) cross-linking and immunoprecipitation (CLIP) allows us to determine physical protein-RNA interactions on a genome-wide scale. UV cross-linking introduces covalent bonds between interacting RBPs and RNAs. In combination with immunoprecipitation and deep sequencing techniques, tens of millions of short reads (representing bound RNAs by an RBP of interest) are generated and are used to characterize the regulatory network mediated by an RBP. Other methods, such as mass spectrometry, can also be used for characterization of cross-linked RBPs and RNAs instead of CLIP methods. In this review, we discuss experimental and computational methods for the generation and analysis of CLIP data. The computational methods include short-read alignment, annotation and RNA-binding motif discovery. We describe the challenges of analyzing CLIP data and indicate areas where improvements are needed.

Indexed as

Gene Expression RegulationTranscription, GeneticBase SequenceComputational BiologyDatabases, GeneticMolecular Sequence DataRNARNA-Binding ProteinsSoftwareRNARNA-Binding Proteinscross-linking and immunoprecipitationNext-generation sequencingposttranscriptional gene regulationRNA-binding motif discovery

Identifiers

PMID24951655
PMCPMC4471435

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.