Evidence map›Paper›PMID 28484236›Full record

ArticleScientific reports2017

Detecting the Molecular System Signatures of Idiopathic Pulmonary Fibrosis through Integrated Genomic Analysis.

Indu Gangwar, Nitesh Kumar Sharma, Ganesh Panzade, Supriya Awasthi, Anurag Agrawal, Ravi Shankar

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

17 citing papers in PubMed, 40 citations in OpenAlex.

  1. Trial
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  4. Overview of multi-omics approaches for pulmonary sarcoidosis.EC pulmonology and respiratory medicine · 2025
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  5. Getting the Timing Right: Controlling BCL-2 Inhibition as an Antifibrotic Therapy.American journal of respiratory cell and molecular biology · 2024
    Article
  6. Article
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  9. miR-338-3p blocks TGFβ-induced myofibroblast differentiation through the induction of PTEN.American journal of physiology. Lung cellular and molecular physiology · 2022
    Article
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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 3 institutions in 1 country.

Indu GangwarStudio of Computational Biology & Bioinformatics, CSIR-IHBT, Palampur, HP, India.
Nitesh Kumar SharmaStudio of Computational Biology & Bioinformatics, CSIR-IHBT, Palampur, HP, India.
Ganesh PanzadeStudio of Computational Biology & Bioinformatics, CSIR-IHBT, Palampur, HP, India.
Supriya AwasthiStudio of Computational Biology & Bioinformatics, CSIR-IHBT, Palampur, HP, India.
Anurag AgrawalCentre of Excellence for Translational Research in Asthma & Lung Diseases, CSIR-IGIB, Mall Road, Delhi, India.
Ravi ShankarStudio of Computational Biology & Bioinformatics, CSIR-IHBT, Palampur, HP, India. ravish@ihbt.res.in.
Academy of Scientific and Innovative Research · INInstitute of Himalayan Bioresource Technology · INInstitute of Genomics and Integrative Biology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Idiopathic Pulmonary Fibrosis (IPF) is an incurable progressive fibrotic disease of the lungs. We currently lack a systematic understanding of IPF biology and a systems approach may offer new therapeutic insights. Here, for the first time, a large volume of high throughput genomics data has been unified to derive the most common molecular signatures of IPF. A set of 39 differentially expressed genes (DEGs) was found critical to distinguish IPF. Using high confidence evidences and experimental data, system level networks for IPF were reconstructed, involving 737 DEGs found common across at least two independent studies. This all provided one of the most comprehensive molecular system views for IPF underlining the regulatory and molecular consequences associated. 56 pathways crosstalks were identified which included critical pathways with specified directionality. The associated steps gained and lost due to crosstalk during IPF were also identified. A serially connected system of five crucial genes was found, potentially controlled by nine miRNAs and eight transcription factors exclusively in IPF when compared to NSIP and Sarcoidosis. Findings from this study have been implemented into a comprehensive molecular and systems database on IPF to facilitate devising diagnostic and therapeutic solutions for this deadly disease.

Indexed as

Gene Expression ProfilingCluster AnalysisGene Regulatory NetworksGenomicsHumansIdiopathic Pulmonary FibrosisMicroRNAsModels, BiologicalSystems BiologyTranscription FactorsMicroRNAsTranscription Factors

Identifiers

PMID28484236
PMCPMC5431532
OpenAlexW2610677468

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.