ArticleNucleic acids research2011
ChIP-Array: combinatory analysis of ChIP-seq/chip and microarray gene expression data to discover direct/indirect targets of a transcription factor.
Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- A self-attention-driven deep learning framework for inference of transcriptional gene regulatory networks.Briefings in bioinformatics · 2024Article
- White-opaque switching inMicrobiology and molecular biology reviews : MMBR · 2024Review
- DNA- and RNA-Binding Proteins Linked Transcriptional Control and Alternative Splicing Together in a Two-Layer Regulatory Network System of Chronic Myeloid Leukemia.Frontiers in molecular biosciences · 2022Article
- Integrating binding and expression data to predict transcription factors combined function.BMC genomics · 2020Article
- Rhizosphere microbiome: Engineering bacterial competitiveness for enhancing crop production.Journal of advanced research · 2020Review
- DLX1 acts as a crucial target of FOXM1 to promote ovarian cancer aggressiveness by enhancing TGF-β/SMAD4 signaling.Oncogene · 2017Article
- Genome-Wide Targets Regulated by the OsMADS1 Transcription Factor Reveals Its DNA Recognition Properties.Plant physiology · 2016Article
- Binding Sites in the EFG1 Promoter for Transcription Factors in a Proposed Regulatory Network: A Functional Analysis in the White and Opaque Phases of Candida albicans.G3 (Bethesda, Md.) · 2016Article
- CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms.Nucleic acids research · 2016Article
- Analysis of miRNA, mRNA, and TF interactions through network-based methods.EURASIP journal on bioinformatics & systems biology · 2015Article
- Microarray and ChIP-seq data analysis revealed changes in p53-mediated transcriptional regulation in Nutlin-3-treated U2OS cells.Molecular medicine reports · 2015Article
- ChIP-Array 2: integrating multiple omics data to construct gene regulatory networks.Nucleic acids research · 2015Article
- Dynamics in Transcriptomics: Advancements in RNA-seq Time Course and Downstream Analysis.Computational and structural biotechnology journal · 2015Review
- SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples.Nucleic acids research · 2014Article
- PTHGRN: unraveling post-translational hierarchical gene regulatory networks using PPI, ChIP-seq and gene expression data.Nucleic acids research · 2014Article
- Oct-2 transcription factor binding activity and expression up-regulation in rat cerebral ischaemia is associated with a diminution of neuronal damage in vitro.Neuromolecular medicine · 2014Article
- YTRP: a repository for yeast transcriptional regulatory pathways.Database : the journal of biological databases and curation · 2014Article
- Large-scale investigation of human TF-miRNA relations based on coexpression profiles.BioMed research international · 2014Article
- Understanding gene regulatory mechanisms by integrating ChIP-seq and RNA-seq data: statistical solutions to biological problems.Frontiers in cell and developmental biology · 2014Article
- DPRP: a database of phenotype-specific regulatory programs derived from transcription factor binding data.Nucleic acids research · 2014Article
Corrections and comments
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Chromatin immunoprecipitation (ChIP) coupled with high-throughput techniques (ChIP-X), such as next generation sequencing (ChIP-Seq) and microarray (ChIP-chip), has been successfully used to map active transcription factor binding sites (TFBS) of a transcription factor (TF). The targeted genes can be activated or suppressed by the TF, or are unresponsive to the TF. Microarray technology has been used to measure the actual expression changes of thousands of genes under the perturbation of a TF, but is unable to determine if the affected genes are direct or indirect targets of the TF. Furthermore, both ChIP-X and microarray methods produce a large number of false positives. Combining microarray expression profiling and ChIP-X data allows more effective TFBS analysis for studying the function of a TF. However, current web servers only provide tools to analyze either ChIP-X or expression data, but not both. Here, we present ChIP-Array, a web server that integrates ChIP-X and expression data from human, mouse, yeast, fruit fly and Arabidopsis. This server will assist biologists to detect direct and indirect target genes regulated by a TF of interest and to aid in the functional characterization of the TF. ChIP-Array is available at http://jjwanglab.hku.hk/ChIP-Array, with free access to academic users.
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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.