ArticleScientific reports2016
Construction and application of a co-expression network in Mycobacterium tuberculosis.
Article in Scientific reports, 2016. 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 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 47 citations in OpenAlex.
- Identification of immunoheterogeneous key prognostic protein ZC3H12D in OSCC and analysis of prognostic models and drug resistance.Discover oncology · 2025Article
- A gene network-driven approach to infer novel pathogenicity-associated genes: application tomSystems · 2023Article
- Anti-TNF Therapy Regulates Phagosome Pathway by Inhibiting NCF4 Expression to Treat Ankylosing Spondylitis.Journal of musculoskeletal & neuronal interactions · 2023Article
- Gene co-expression network construction and analysis for identification of genetic biomarkers associated with glioblastoma multiforme using topological findings.Journal of the Egyptian National Cancer Institute · 2023Article
- Down-regulated C4orf19 confers poor prognosis in colon adenocarcinoma identified by gene co-expression network.Journal of Cancer · 2022Article
- Gene co-expression network analysis of the human gut commensal bacterium Faecalibacterium prausnitzii in R-Shiny.PloS one · 2022Article
- Surviving in the Brine: A Multi-Omics Approach for Understanding the Physiology of the Halophile FungusFrontiers in microbiology · 2022Article
- Article
- CD8Journal of oncology · 2021Article
- Identification of CD8+ T Cell-Related Genes: Correlations with Immune Phenotypes and Outcomes of Liver Cancer.Journal of immunology research · 2021Article
- Article
- CD8+ T Cell Co-Expressed Genes Correlate With Clinical Phenotype and Microenvironments of Urothelial Cancer.Frontiers in oncology · 2020Article
- Construction, analysis and validation of co-expression network to understand stress adaptation in Deinococcus radiodurans R1.PloS one · 2020Article
- The Construction and Analysis of lncRNA-miRNA-mRNA Competing Endogenous RNA Network of Schwann Cells in Diabetic Peripheral Neuropathy.Frontiers in bioengineering and biotechnology · 2020Article
- Genome-wide analysis of yeast expression data based on a priori generated co-regulation cliques.Microbial cell (Graz, Austria) · 2019Article
- Reconstruction and inference of the Lactococcus lactis MG1363 gene co-expression network.PloS one · 2019Article
- Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.BMC genomics · 2018Article
- Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Because of its high pathogenicity and infectivity, tuberculosis is a serious threat to human health. Some information about the functions of the genes in Mycobacterium tuberculosis genome was currently available, but it was not enough to explore transcriptional regulatory mechanisms. Here, we applied the WGCNA (Weighted Gene Correlation Network Analysis) algorithm to mine pooled microarray datasets for the M. tuberculosis H37Rv strain. We constructed a co-expression network that was subdivided into 78 co-expression gene modules. The different response to two kinds of vitro models (a constant 0.2% oxygen hypoxia model and a Wayne model) were explained based on these modules. We identified potential transcription factors based on high Pearson's correlation coefficients between the modules and genes. Three modules that may be associated with hypoxic stimulation were identified, and their potential transcription factors were predicted. In the validation experiment, we determined the expression levels of genes in the modules under hypoxic condition and under overexpression of potential transcription factors (Rv0081, furA (Rv1909c), Rv0324, Rv3334, and Rv3833). The experimental results showed that the three identified modules related to hypoxia and that the overexpression of transcription factors could significantly change the expression levels of genes in the corresponding modules.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.