ArticleGenome research2006
A computational genomics approach to identify cis-regulatory modules from chromatin immunoprecipitation microarray data--a case study using E2F1.
Article in Genome research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
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- An Expanded Interplay Network between NF-κB p65 (RelA) and E2F1 Transcription Factors: Roles in Physiology and Pathology.Cancers · 2022Article
- AP-2α-Mediated Activation of E2F and EZH2 Drives Melanoma Metastasis.Cancer research · 2021Article
- The CLN3 gene and protein: What we know.Molecular genetics & genomic medicine · 2019Review
- Genome-wide analysis of the oxyntic proliferative isthmus zone reveals ASPM as a possible gastric stem/progenitor cell marker over-expressed in cancer.The Journal of pathology · 2015Article
- E2F2 and CREB cooperatively regulate transcriptional activity of cell cycle genes.Nucleic acids research · 2013Article
- Network insights into the genes regulated by hepatocyte nuclear factor 4 in response to drug induced perturbations: a review.Current drug discovery technologies · 2013Review
- Targeting BIG3-PHB2 interaction to overcome tamoxifen resistance in breast cancer cells.Nature communications · 2013Article
- Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions.PLoS computational biology · 2013Article
- Evidence for autoregulation and cell signaling pathway regulation from genome-wide binding of the Drosophila retinoblastoma protein.G3 (Bethesda, Md.) · 2012Article
- Uncovering transcription factor modules using one- and three-dimensional analyses.The Journal of biological chemistry · 2012Review
- DNA damage-induced activation of ATM promotes β-TRCP-mediated Mdm2 ubiquitination and destruction.Oncotarget · 2012Article
- Regulation of matrix metalloproteinase genes by E2F transcription factors: Rb-Raf-1 interaction as a novel target for metastatic disease.Cancer research · 2012Article
- Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.Scientific reports · 2012Article
- A modulated empirical Bayes model for identifying topological and temporal estrogen receptor α regulatory networks in breast cancer.BMC systems biology · 2011Article
- Motif-guided sparse decomposition of gene expression data for regulatory module identification.BMC bioinformatics · 2011Article
- W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data.Bioinformatics (Oxford, England) · 2011Article
- ChIP-seq defined genome-wide map of TGFβ/SMAD4 targets: implications with clinical outcome of ovarian cancer.PloS one · 2011Article
- Rb/E2F regulates expression of neogenin during neuronal migration.Molecular and cellular biology · 2011Article
- Genome-wide binding of the orphan nuclear receptor TR4 suggests its general role in fundamental biological processes.BMC genomics · 2010Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Advances in high-throughput technologies, such as ChIP-chip, and the completion of human and mouse genomic sequences now allow analysis of the mechanisms of gene regulation on a systems level. In this study, we have developed a computational genomics approach (termed ChIPModules), which begins with experimentally determined binding sites and integrates positional weight matrices constructed from transcription factor binding sites, a comparative genomics approach, and statistical learning methods to identify transcriptional regulatory modules. We began with E2F1 binding site information obtained from ChIP-chip analyses of ENCODE regions, from both HeLa and MCF7 cells. Our approach not only distinguished targets from nontargets with a high specificity, but it also identified five regulatory modules for E2F1. One of the identified modules predicted a colocalization of E2F1 and AP-2alpha on a set of target promoters with an intersite distance of <270 bp. We tested this prediction using ChIP-chip assays with arrays containing approximately 14,000 human promoters. We found that both E2F1 and AP-2alpha bind within the predicted distance to a large number of human promoters, demonstrating the strength of our sequence-based, unbiased, and universal protocol. Finally, we have used our ChIPModules approach to develop a database that includes thousands of computationally identified and/or experimentally verified E2F1 target promoters.
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