ArticleGenome research2006
A systematic model to predict transcriptional regulatory mechanisms based on overrepresentation of transcription factor binding profiles.
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 44 papers.
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Who cites it
44 citing papers in PubMed, 74 citations in OpenAlex.
- Identification of upstream transcription factor binding sites in orthologous genes using mixed Student's t-test statistics.PLoS computational biology · 2022Article
- Systematic identification of genes associated with plant growth-defense tradeoffs under JA signaling in Arabidopsis.Planta · 2020Article
- TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network.BMC bioinformatics · 2017Article
- Actin and Keratin are Binding Partners of the 1,25DImmunology, endocrine & metabolic agents in medicinal chemistry · 2014Article
- An integrated approach to characterize transcription factor and microRNA regulatory networks involved in Schwann cell response to peripheral nerve injury.BMC genomics · 2013Article
- Using graph models to find transcription factor modules: the hitting set problem and an exact algorithm.Algorithms for molecular biology : AMB · 2013Article
- Genetic predisposition in NAFLD and NASH: impact on severity of liver disease and response to treatment.Current pharmaceutical design · 2013Article
- Uncovering cis-regulatory sequence requirements for context-specific transcription factor binding.Genome research · 2012Article
- Interleukin-1β modulates smooth muscle cell phenotype to a distinct inflammatory state relative to PDGF-DD via NF-κB-dependent mechanisms.Physiological genomics · 2012Article
- Conserved Motifs and Prediction of Regulatory Modules in Caenorhabditis elegans.G3 (Bethesda, Md.) · 2012Article
- Evolutionary divergence and limits of conserved non-coding sequence detection in plant genomes.Nucleic acids research · 2011Article
- Identification of transcriptional regulatory networks specific to pilocytic astrocytoma.BMC medical genomics · 2011Article
- BiologicalNetworks--tools enabling the integration of multi-scale data for the host-pathogen studies.BMC systems biology · 2011Article
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- CCAAT/enhancer-binding protein β and NF-κB mediate high level expression of chemokine genes CCL3 and CCL4 by human chondrocytes in response to IL-1β.The Journal of biological chemistry · 2010Article
- Highly conserved transcriptional responses to mechanical ventilation of the lung.Physiological genomics · 2010Article
- Resistin induces expression of proinflammatory cytokines and chemokines in human articular chondrocytes via transcription and messenger RNA stabilization.Arthritis and rheumatism · 2010Article
- TFM-Explorer: mining cis-regulatory regions in genomes.Nucleic acids research · 2010Article
- Identification of functional TFAP2A and SP1 binding sites in new TFAP2A-modulated genes.BMC genomics · 2010Article
- Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data.BMC bioinformatics · 2010Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
An important aspect of understanding a biological pathway is to delineate the transcriptional regulatory mechanisms of the genes involved. Two important tasks are often encountered when studying transcription regulation, i.e., (1) the identification of common transcriptional regulators of a set of coexpressed genes; (2) the identification of genes that are regulated by one or several transcription factors. In this study, a systematic and statistical approach was taken to accomplish these tasks by establishing an integrated model considering all of the promoters and characterized transcription factors (TFs) in the genome. A promoter analysis pipeline (PAP) was developed to implement this approach. PAP was tested using coregulated gene clusters collected from the literature. In most test cases, PAP identified the transcription regulators of the input genes accurately. When compared with chromatin immunoprecipitation experiment data, PAP's predictions are consistent with the experimental observations. When PAP was used to analyze one published expression-profiling data set and two novel coregulated gene sets, PAP was able to generate biologically meaningful hypotheses. Therefore, by taking a systematic approach of considering all promoters and characterized TFs in our model, we were able to make more reliable predictions about the regulation of gene expression in mammalian organisms.
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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.