The genome-level in vivo approaches to analyzing σ-specific regulons using microarrays or ChIP-chip techniques may therefore be negatively affected by these regulatory interactions.
The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics, are becoming vast.
By combining chromatin immunoprecipitation (ChIP) with high throughput sequencing or DNA microarrays (ChIP-Seq or ChIP-chip), it is possible to query the genomic localizations of specific transcription factors, histone modifications, and chromatin remodelling factors.
Mass data from such experiments, e.g., DNA microarray, yeast two-hybrid or ChIP-chip assay, possess considerable challenges for their statistical data analysis.
In general, "genomics data" refers to genome-scale vector of measurements produced by various experimental assays (expression microarrays, CGH microarrays, ChIP-chip and ChIP-seq, etc).
ChIP assay followed by next generation sequencing (ChIP-seq) or microarray (ChIP-chip) is often used to study patterns of protein-binding profiles in different cell types and in cancer samples on a genome-wide scale.
The recent advancement of experimental technologies such as chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) [ 26] or microarray hybridization (ChIP-chip) [ 27] enables us to more accurately determine genome wide occupation of TFs.
We have examined the genomic relationship between STAT1 binding and regulated transcription using multiple tiling microarray and chromatin immunoprecipitation microarray (ChIP-chip) experiments from public repositories.
Chromatin immunoprecipitation combined with either microarray hybridization (ChIP-chip) or sequencing (ChIP-seq) allows to determine genomic association of DNA binding proteins and to analyze epigenetic regulation [1], [2], [3].
Current chromatin immunoprecipitation (ChIP) technologies coupled with microarray hybridization (ChIP-chip) or parallel DNA sequencing (ChIP-seq) enable the identification of transcription factor-binding sites in vivo in the genome-wide scale.
