Evidence map›Paper›PMID 26734617›Full record

ReviewFrontiers in molecular biosciences2015

Stem Cell Ribonomics: RNA-Binding Proteins and Gene Networks in Stem Cell Differentiation.

Patrícia Shigunov, Bruno Dallagiovanna

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Poly(A) tail regulation in stem cells and early development.Cell regeneration (London, England) · 2025
    Review
  2. Article
  3. Article
  4. Regulation of CD8 T Cell Differentiation by the RNA-Binding Protein DDX5.Journal of immunology (Baltimore, Md. : 1950) · 2023
    Article
  5. Primordial Germ Cell Development in the Poeciliid,Frontiers in cell and developmental biology · 2022
    Article
  6. Article
  7. Article
  8. Review
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

2 authors at 2 institutions in 1 country.

Patrícia ShigunovStem Cells Basic Biology Laboratory, Carlos Chagas Institute, Oswaldo Cruz Foundation Curitiba, Brazil.
Bruno DallagiovannaStem Cells Basic Biology Laboratory, Carlos Chagas Institute, Oswaldo Cruz Foundation Curitiba, Brazil.
Fundação Carlos Chagas · BRFundação Oswaldo Cruz · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stem cells are undifferentiated cells with the ability to self-renew and the potential to differentiate into all body cell types. Stem cells follow a developmental genetic program and are able to respond to alterations in the environment through various signaling pathways. The mechanisms that control these processes involve the activation of transcription followed by a series of post-transcriptional events. These post-transcriptional steps are mediated by the interaction of RNA-binding proteins (RBPs) with defined subpopulations of RNAs creating a regulatory gene network. Characterizing these RNA-protein networks is essential to understanding the regulatory mechanisms underlying the control of stem cell fate. Ribonomics is the combination of classical biochemical purification protocols with the high-throughput identification of transcripts applied to the functional characterization of RNA-protein complexes. Here, we describe the different approaches that can be used in a ribonomic approach and how they have contributed to understanding the function of several RBPs with central roles in stem cell biology.

Indexed as

differentiationgene networkribonomicsRNA-binding proteinsstem cells

Identifiers

PMID26734617
PMCPMC4686646
OpenAlexW2226475699

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.