Evidence map›Paper›PMID 23387820›Full record

ArticleBMC genomics2013

An integrated approach to characterize transcription factor and microRNA regulatory networks involved in Schwann cell response to peripheral nerve injury.

Li-Wei Chang, Andreu Viader, Nobish Varghese, Jacqueline E Payton, Jeffrey Milbrandt, Rakesh Nagarajan

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.4field-weighted citation impact, top 23% 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

22 citing papers in PubMed, 38 citations in OpenAlex.

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  17. Transcriptomic Approaches to Neural Repair.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015
    Review
  18. Article
  19. The role of exosomes in peripheral nerve regeneration.Neural regeneration research · 2015
    Review
  20. Article
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

6 authors at 1 institution in 1 country.

Li-Wei ChangDepartment of Pathology and Immunology, Washington University School of Medicine, 660 South Euclid Ave, St, Louis, MO 63110, USA.
Andreu Viader
Nobish Varghese
Jacqueline E Payton
Jeffrey Milbrandt
Rakesh Nagarajan
Washington University in St. Louis · US

Funding

PHYSIOLOGY AND GENETICS OF THE GDNF HOMOLOG NEURTURINR01AG013730 · NIA · WASHINGTON UNIVERSITY · PI JEFFREY D MILBRANDT · 1996 to 2026
$10.6M
Washington University Center for Translational NeuroscienceP30NS057105 · NINDS · WASHINGTON UNIVERSITY · PI HOLTZMAN, DAVID M. · 2006 to 2011
$8.7M
ROLE OF EGR2 MUTATIONS IN PERIPHERAL MYELINOPATHIESR01NS040745 · NINDS · WASHINGTON UNIVERSITY · PI MILBRANDT, JEFFREY D · 2001 to 2009
$3.3M
Novel Bioinformatics Tools for Gene Regulatory Network InferenceK99LM010824 · NLM · WASHINGTON UNIVERSITY · PI CHANG, LI-WEI · 2010 to 2011
$180k
NIA NIH HHS AG13730NIA NIH HHS R01 AG013730NINDS NIH HHS NS040745NINDS NIH HHS P30NS057105NLM NIH HHS K99LM010824
6 · The paper itself

Abstract

backgroundThe regenerative response of Schwann cells after peripheral nerve injury is a critical process directly related to the pathophysiology of a number of neurodegenerative diseases. This SC injury response is dependent on an intricate gene regulatory program coordinated by a number of transcription factors and microRNAs, but the interactions among them remain largely unknown. Uncovering the transcriptional and post-transcriptional regulatory networks governing the Schwann cell injury response is a key step towards a better understanding of Schwann cell biology and may help develop novel therapies for related diseases. Performing such comprehensive network analysis requires systematic bioinformatics methods to integrate multiple genomic datasets.

resultsIn this study we present a computational pipeline to infer transcription factor and microRNA regulatory networks. Our approach combined mRNA and microRNA expression profiling data, ChIP-Seq data of transcription factors, and computational transcription factor and microRNA target prediction. Using mRNA and microRNA expression data collected in a Schwann cell injury model, we constructed a regulatory network and studied regulatory pathways involved in Schwann cell response to injury. Furthermore, we analyzed network motifs and obtained insights on cooperative regulation of transcription factors and microRNAs in Schwann cell injury recovery.

conclusionsThis work demonstrates a systematic method for gene regulatory network inference that may be used to gain new information on gene regulation by transcription factors and microRNAs.

Indexed as

Gene Regulatory NetworksAnimalsChromatin ImmunoprecipitationComputational BiologyEarly Growth Response Protein 2Gene Expression ProfilingGene Expression RegulationGenomicsHumansMiceMicroRNAsMyelin SheathPeripheral Nerve InjuriesRNA, MessengerSchwann CellsTranscription FactorsEarly Growth Response Protein 2MicroRNAsRNA, MessengerTranscription Factors

Identifiers

PMID23387820
PMCPMC3599357
OpenAlexW1971790889

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.