scholarly journals ELMER v.2: An R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles

2017 ◽  
Author(s):  
Tiago C Silva ◽  
Simon G Coetzee ◽  
Lijing Yao ◽  
Nicole Gull ◽  
Dennis J Hazelett ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Bioconductor Package ◽  
Web Based ◽  
Functional Changes ◽  
Regulatory Modules ◽  
Gene Regulatory ◽  
Altered Gene ◽  
Analysis Mode

AbstractMotivationDNA methylation has been used to identify functional changes at transcriptional enhancers and other cis-regulatory modules (CRMs) in tumors and other disease tissues. Our R/Bioconductor packageELMER(Enhancer Linking by Methylation/Expression Relationships) provides a systematic approach that reconstructs altered gene regulatory networks (GRNs) by combining enhancer methylation and gene expression data derived from the same sample set.ResultsWe present a completely revised version 2 ofELMERthat provides numerous new features including an optional web-based interface and a new Supervised Analysis mode to use pre-defined sample groupings. We show that this approach can identify GRNs associated with many new Master Regulators includingKLF5in breast cancer.AvailabilityELMERv.2 is available as an R/Bioconductor package athttp://bioconductor.org/packages/ELMER/

scholarly journals ELMER v.2: an R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles

2018 ◽  
Vol 35 (11) ◽  
pp. 1974-1977 ◽  
Author(s):  
Tiago C Silva ◽  
Simon G Coetzee ◽  
Nicole Gull ◽  
Lijing Yao ◽  
Dennis J Hazelett ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Gene Regulatory Networks ◽  
Statistical Power ◽  
Regulatory Networks ◽  
Supplementary Information ◽  
Bioconductor Package ◽  
Functional Changes ◽  
Basal Like Breast Cancer ◽  
Gene Regulatory ◽  
Altered Gene

Abstract Motivation DNA methylation has been used to identify functional changes at transcriptional enhancers and other cis-regulatory modules (CRMs) in tumors and other disease tissues. Our R/Bioconductor package ELMER (Enhancer Linking by Methylation/Expression Relationships) provides a systematic approach that reconstructs altered gene regulatory networks (GRNs) by combining enhancer methylation and gene expression data derived from the same sample set. Results We present a completely revised version 2 of ELMER that provides numerous new features including an optional web-based interface and a new Supervised Analysis mode to use pre-defined sample groupings. We show that Supervised mode significantly increases statistical power and identifies additional GRNs and associated Master Regulators, such as SOX11 and KLF5 in Basal-like breast cancer. Availability and implementation ELMER v.2 is available as an R/Bioconductor package at http://bioconductor.org/packages/ELMER/. Supplementary information Supplementary data are available at Bioinformatics online.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks

2014 ◽  
Vol 20 (12) ◽  
pp. 1903-1912 ◽  
Author(s):  
Bowen Yu ◽  
Harish Doraiswamy ◽  
Xi Chen ◽  
Emily Miraldi ◽  
Mario Luis Arrieta-Ortiz ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Visual Exploration ◽  
Web Based ◽  
Gene Regulatory

scholarly journals ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks

2015 ◽  
Vol 16 (Suppl 9) ◽  
pp. S7 ◽  
Author(s):  
Gianvito Pio ◽  
Michelangelo Ceci ◽  
Donato Malerba ◽  
Domenica D'Elia
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Mirna Gene ◽  
Web Based ◽  
Gene Regulatory ◽  
Web Based System

scholarly journals DNA methylation and gene expression profiles to identify childhood atopic asthma associated genes

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rui Chen ◽  
Li-Zhen Piao ◽  
Ling Liu ◽  
Xiao-Fei Zhang
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Gene ◽  
Atopic Asthma ◽  
Mirna Target Gene ◽  
Kegg Pathways ◽  
Gene Regulatory

Abstract Background Asthma is a chronic inflammatory disorder of the airways involving many different factors. This study aimed to screen for the critical genes using DNA methylation/CpGs and miRNAs involved in childhood atopic asthma. Methods DNA methylation and gene expression data (Access Numbers GSE40732 and GSE40576) were downloaded from the Gene Expression Omnibus database. Each set contains 194 peripheral blood mononuclear cell (PBMC) samples of 97 children with atopic asthma and 97 control children. Differentially expressed genes (DEGs) with DNA methylation changes were identified. Pearson correlation analysis was used to select genes with an opposite direction of expression and differences in methylation levels, and then Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Protein–protein interaction network and miRNA–target gene regulatory networks were then constructed. Finally, important genes related to asthma were screened. Results A total of 130 critical DEGs with DNA methylation changes were screened from children with atopic asthma and compared with control samples from healthy children. GO and KEGG pathway enrichment analysis found that critical genes were primarily related to 24 GO terms and 10 KEGG pathways. In the miRNA–target gene regulatory networks, 9 KEGG pathways were identified. Analysis of the miRNA–target gene network noted an overlapping KEGG signaling pathway, hsa04060: cytokine-cytokine receptor interaction, in which the gene CCL2, directly related to asthma, was involved. This gene is targeted by eight asthma related miRNAs (hsa-miR-206, hsa-miR-19a, hsa-miR-9,hsa-miR-22, hsa-miR-33b, hsa-miR-122, hsa-miR-1, and hsa-miR-23b). The genes IL2RG and CCl4 were also involved in this pathway. Conclusions The present study provides a novel insight into the underlying molecular mechanism of childhood atopic asthma.

scholarly journals A mathematical model exhibiting the effect of DNA methylation on the stability boundary in cell-fate networks

2019 ◽  
Author(s):  
Tianchi Chen ◽  
Muhammad Ali Al-Radhawi ◽  
Eduardo Sontag
Keyword(s):  
Mathematical Model ◽  
Dna Methylation ◽  
Gene Silencing ◽  
Cell Fate ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Stability Boundary ◽  
Basin Of Attraction ◽  
Gene Regulatory ◽  
The Stability

Cell-fate networks are traditionally studied within the framework of gene regulatory networks. This paradigm considers only interactions of genes through expressed transcription factors and does not incorporate chromatin modification processes. This paper introduces a mathematical model that seamlessly combines gene regulatory networks and DNA methylation, with the goal of quantitatively characterizing the contribution of epigenetic regulation to gene silencing. The "Basin of Attraction percentage'' is introduced as a metric to quantify gene silencing abilities. As a case study, a computational and theoretical analysis is carried out for a model of the pluripotent stem cell circuit as well as a simplified self-activating gene model. The results confirm that the methodology quantitatively captures the key role that methylation plays in enhancing the stability of the silenced gene state.

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