ArticleEnvironmental health perspectives2004
Gene interaction network suggests dioxin induces a significant linkage between aryl hydrocarbon receptor and retinoic acid receptor beta.
Article in Environmental health perspectives, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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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.
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Who cites it
11 citing papers in PubMed.
- A novel method to identify differential pathways in uterine leiomyomata based on network strategy.Oncology letters · 2017Article
- The additive effects of theOncotarget · 2017Article
- Construction of protein interaction network involved in lung adenocarcinomas using a novel algorithm.Oncology letters · 2016Article
- Multi-parametric profiling network based on gene expression and phenotype data: a novel approach to developmental neurotoxicity testing.International journal of molecular sciences · 2012Article
- Identification of Stage-Specific Gene Expression Signatures in Response to Retinoic Acid during the Neural Differentiation of Mouse Embryonic Stem Cells.Frontiers in genetics · 2012Article
- Oxygenomics in environmental stress.Redox report : communications in free radical research · 2010Review
- AhR-mediated gene expression in the developing mouse telencephalon.Reproductive toxicology (Elmsford, N.Y.) · 2009Article
- Characteristics of transcriptional activity in nonlinear dynamics of genetic regulatory networks.Gene regulation and systems biology · 2009Article
- Characterization of the proneural gene regulatory network during mouse telencephalon development.BMC biology · 2008Article
- Systems biology: new approaches to old environmental health problems.International journal of environmental research and public health · 2005Article
- The TAO-Gen algorithm for identifying gene interaction networks with application to SOS repair in E. coli.Environmental health perspectives · 2004Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Gene expression arrays (gene chips) have enabled researchers to roughly quantify the level of mRNA expression for a large number of genes in a single sample. Several methods have been developed for the analysis of gene array data including clustering, outlier detection, and correlation studies. Most of these analyses are aimed at a qualitative identification of what is different between two samples and/or the relationship between two genes. We propose a quantitative, statistically sound methodology for the analysis of gene regulatory networks using gene expression data sets. The method is based on Bayesian networks for direct quantification of gene expression networks. Using the gene expression changes in HPL1A lung airway epithelial cells after exposure to 2,3,7,8-tetrachlorodibenzo-(Italic)p(/Italic)-dioxin at levels of 0.1, 1.0, and 10.0 nM for 24 hr, a gene expression network was hypothesized and analyzed. The method clearly demonstrates support for the assumed network and the hypothesis linking the usual dioxin expression changes to the retinoic acid receptor system. Simulation studies demonstrated the method works well, even for small samples.
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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.