Mining ChIP-chip data for transcription factor and cofactor binding sites

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Mining ChIP-chip data for transcription factor and cofactor binding sites

MOTIVATION Identification of single motifs and motif pairs that can be used to predict transcription factor localization in ChIP-chip data, and gene expression in tissue-specific microarray data. RESULTS We describe methodology to identify de novo individual and interacting pairs of binding site motifs from ChIP-chip data, using an algorithm that integrates localization data directly into the...

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ChIP-Chip: algorithms for calling binding sites.

Genome-wide ChIP-chip assays of protein-DNA interactions yield large volumes of data requiring effective statistical analysis to obtain reliable results. Successful analysis methods need to be tailored to platform specific characteristics such as probe density, genome coverage, and the nature of the controls. We describe the use of the respective software packages MAT and MA2C for the analysis ...

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From binding motifs in Chip-seq Data to Improved Models of transcription factor binding Sites

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) became a method of choice to locate DNA segments bound by different regulatory proteins. ChIP-Seq produces extremely valuable information to study transcriptional regulation. The wet-lab workflow is often supported by downstream computational analysis including construction of models of nucleotide sequences of transcription fa...

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dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data

Chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) has been successfully used for genome-wide profiling of transcription factor binding sites, histone modifications, and nucleosome occupancy in many model organisms and humans. Because the compact genomes of prokaryotes harbor many binding sites separated by only few base pairs, applications of ChIP-Seq in this domai...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2005

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/bti1043