Evidence map›Paper›PMID 27252657›Full record

ArticleFrontiers in physiology2016

Community Structure Reveals Biologically Functional Modules in MEF2C Transcriptional Regulatory Network.

Sergio A Alcalá-Corona, Tadeo E Velázquez-Caldelas, Jesús Espinal-Enríquez, Enrique Hernández-Lemus

Abstract read
In one paragraph

Article in Frontiers in physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  9. Modularity in Biological Networks.Frontiers in genetics · 2021
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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

4 authors.

Sergio A Alcalá-CoronaComputational Genomics Department, National Institute of Genomic MedicineMexico City, Mexico; Complexity in Systems Biology, Center for Complexity Sciences, Universidad Nacional Autónoma de MéxicoMexico City, Mexico.
Tadeo E Velázquez-CaldelasComputational Genomics Department, National Institute of Genomic Medicine Mexico City, Mexico.
Jesús Espinal-EnríquezComputational Genomics Department, National Institute of Genomic MedicineMexico City, Mexico; Complexity in Systems Biology, Center for Complexity Sciences, Universidad Nacional Autónoma de MéxicoMexico City, Mexico.
Enrique Hernández-LemusComputational Genomics Department, National Institute of Genomic MedicineMexico City, Mexico; Complexity in Systems Biology, Center for Complexity Sciences, Universidad Nacional Autónoma de MéxicoMexico City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene regulatory networks are useful to understand the activity behind the complex mechanisms in transcriptional regulation. A main goal in contemporary biology is using such networks to understand the systemic regulation of gene expression. In this work, we carried out a systematic study of a transcriptional regulatory network derived from a comprehensive selection of all potential transcription factor interactions downstream from MEF2C, a human transcription factor master regulator. By analyzing the connectivity structure of such network, we were able to find different biologically functional processes and specific biochemical pathways statistically enriched in communities of genes into the network, such processes are related to cell signaling, cell cycle and metabolism. In this way we further support the hypothesis that structural properties of biological networks encode an important part of their functional behavior in eukaryotic cells.

Indexed as

community structureFANTOM4InfoMapMEF2Ctranscriptional regulatory networkstranscription factor

Identifiers

PMID27252657
PMCPMC4878384

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.