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We are analyzing https://www.nature.com/articles/nmeth.1246.

Title:
Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data | Nature Methods
Description:
A chromatin immunoprecipitation and sequencing (ChIP-Seq) data analysis package, QuEST, facilitates transcription factor binding site discovery at about 20-base-pair resolution. Molecular interactions between protein complexes and DNA mediate essential gene-regulatory functions. Uncovering such interactions by chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) has recently become the focus of intense interest. We here introduce quantitative enrichment of sequence tags (QuEST), a powerful statistical framework based on the kernel density estimation approach, which uses ChIP-Seq data to determine positions where protein complexes contact DNA. Using QuEST, we discovered several thousand binding sites for the human transcription factors SRF, GABP and NRSF at an average resolution of about 20 base pairs. MEME motif-discovery tool–based analyses of the QuEST-identified sequences revealed DNA binding by cofactors of SRF, providing evidence that cofactor binding specificity can be obtained from ChIP-Seq data. By combining QuEST analyses with Gene Ontology (GO) annotations and expression data, we illustrate how general functions of transcription factors can be inferred.
Website Age:
30 years and 10 months (reg. 1994-08-11).

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🚀🌠 Tremendous Traffic: 10M - 20M visitors per month


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Keywords {🔍}

article, google, scholar, cas, nature, transcription, data, methods, binding, factor, access, cell, gene, content, sites, chipseq, myers, dna, human, genome, stanford, cookies, analysis, genomewide, johnson, chromatin, quest, privacy, anton, sidow, interactions, factors, srf, nat, res, supplementary, information, valouev, arend, immunoprecipitation, sequencing, sequence, open, california, usa, author, advertising, subscribe, based, david,

Topics {✒️}

nature portfolio permissions reprints privacy policy advertising nature 447 nature social media neuron-restrictive silencer factor vivo protein-dna interactions gc-rich repressor element dispersed chip-seq data transcription factor binding serum response factor author correspondence potential target genes cooperative binding related springerlink instant access nrsf/rest repressor network thousand binding sites permissions protein-dna interactions neuronal gene transcription human bidirectional promoters chip-seq data �stripe” transcription factors protein-protein interactions single conserved sites cofactor binding specificity dna microarray hybridization stat1 dna association predefined dna targets corepressors mediate plasticity privacy combining quest analyses svm-based algorithm neuronal gene chromatin massively parallel sequencing high-resolution profiling signal transduction article valouev explore content subscription content human cell types european economic area issue learn institutional subscriptions read encode pilot project preliminary statistical framework personal data expression data

Schema {🗺️}

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         description:A chromatin immunoprecipitation and sequencing (ChIP-Seq) data analysis package, QuEST, facilitates transcription factor binding site discovery at about 20-base-pair resolution. Molecular interactions between protein complexes and DNA mediate essential gene-regulatory functions. Uncovering such interactions by chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) has recently become the focus of intense interest. We here introduce quantitative enrichment of sequence tags (QuEST), a powerful statistical framework based on the kernel density estimation approach, which uses ChIP-Seq data to determine positions where protein complexes contact DNA. Using QuEST, we discovered several thousand binding sites for the human transcription factors SRF, GABP and NRSF at an average resolution of about 20 base pairs. MEME motif-discovery tool–based analyses of the QuEST-identified sequences revealed DNA binding by cofactors of SRF, providing evidence that cofactor binding specificity can be obtained from ChIP-Seq data. By combining QuEST analyses with Gene Ontology (GO) annotations and expression data, we illustrate how general functions of transcription factors can be inferred.
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      headline:Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data
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