Genome-Wide Mapping of in Vivo Protein-DNA Interactions

By David S. Johnson, Ali Mortazavi, Richard M. Myers, Barbara J. Wold. Science, 2007

2,946 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c5d15702ed2bed2160e668ce5197c1005db8ca70

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Molecular Biology

Citations in the corpus

Distinct Epigenomic Landscapes of Pluripotent and Lineage-committed Human Cells (2010, methodology): “ChromaSig was used to simultaneously cluster and align all 11 chromatin modifications mapped from both cell types at (A) promoters, (B) predicted enhancers, and (C) regions of ChIP-Seq enriched sequences.”
Applications of next-generation sequencing technologies in functional genomics. (2008, methodology): “To date, ChIPSeq has been applied to the identification of transcription factor binding sites as well as histone modifications on a genome-wide scale [32,34,36,37].”
Genomewide Analysis of PRC1 and PRC2 Occupancy Identifies Two Classes of Bivalent Domains (2008, background): “Notably, the NRSF motif is among the best characterized and highly predictive binding elements in mammalian genomes [42].”
Integration of biological networks and gene expression data using Cytoscape (2007, methodology): “Protein–DNA interactions mapped at the genome scale using ChIP-Chip and ChIPSeq technolog”
oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets (2012, background): “Third, widespread application of ChIP-Seq profiling has resulted in an explosion of the number of potential regulatory sequences to be analyzed (Johnson et al. 2007; Malhotra et al. 2010; Schmidt et al. 2010).”
GREAT improves functional interpretation of cis-regulatory regions (2010, background): “1630" language="eng" relation="no"> The coupling of chromatin immunoprecipitation with massively parallel sequencing, ChIP-seq, is ushering in a new era of genome-wide functional analysi”
Comprehensive Genome-wide Protein-DNA Interactions Detected at Single Nucleotide Resolution (2011, background): “Subsequently, the bound DNA is identified genome-wide by microarray hybridization (ChIP-chip) or deep sequencing (ChIPseq ) (Albert et al., 2007; Johnson et al., 2007; Ren et al., 2000).”
A review on machine learning principles for multi-view biological data integration (2016, background): “For example, whole genome (or exome) sequencing [6] detects single-nucleotide and structural variations (genetic level); ChIP-seq [7] identifies transcription factor binding sites (protein– DNA interactomic level) and histone modifications (epigenomic level) in the entire human genome; DNase-seq [8]”
Ensembl regulation resources (2016, methodology): “…with chromatin immunoprecipitation followed by microarray hybridisation (ChIP-chip) (12) now generally employ high-throughput sequencing (ChIP-seq) (13, 14); DNA methylation is assayed with MeDIP (15) or bisul-phite sequencing (16); regions of open chromatin are identified with…”
Comparison of Next-Generation Sequencing Systems (2012, background): “[34] developed a large-scale chromatin immunoprecipitation assay to identify motif, especially noncanonical NRSFbinding motif.”
A User's Guide to the Encyclopedia of DNA Elements (ENCODE) (2011, methodology): “ChIP-seq enables genome-scale mapping of transcription factor (TF) occupancy patterns in vivo [59,60,62] and is being extensively applied by ENCODE to create an atlas of regulatory factor binding in diverse cell types.”