A signal-noise model for significance analysis of ChIP-seq with negative control.
about
PPARG binding landscapes in macrophages suggest a genome-wide contribution of PU.1 to divergent PPARG binding in human and mouseEvaluation of algorithm performance in ChIP-seq peak detectionPractical guidelines for the comprehensive analysis of ChIP-seq dataA transcriptional repressor co-regulatory network governing androgen response in prostate cancersAgo1 Interacts with RNA polymerase II and binds to the promoters of actively transcribed genes in human cancer cellsComputational characterization of modes of transcriptional regulation of nuclear receptor genesFeatures that define the best ChIP-seq peak calling algorithmsCHANCE: comprehensive software for quality control and validation of ChIP-seq dataDROMPA: easy-to-handle peak calling and visualization software for the computational analysis and validation of ChIP-seq datadiffReps: detecting differential chromatin modification sites from ChIP-seq data with biological replicates.HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data.PePr: a peak-calling prioritization pipeline to identify consistent or differential peaks from replicated ChIP-Seq data.bPeaks: a bioinformatics tool to detect transcription factor binding sites from ChIPseq data in yeasts and other organisms with small genomes.groHMM: a computational tool for identifying unannotated and cell type-specific transcription units from global run-on sequencing data.SCell: integrated analysis of single-cell RNA-seq dataIdentifying peaks in *-seq data using shape information.An integrated functional genomics approach identifies the regulatory network directed by brachyury (T) in chordoma.Q&A: ChIP-seq technologies and the study of gene regulationCo-binding by YY1 identifies the transcriptionally active, highly conserved set of CTCF-bound regions in primate genomesTET1 is a maintenance DNA demethylase that prevents methylation spreading in differentiated cells.A short survey of computational analysis methods in analysing ChIP-seq data.Methods for cancer epigenome analysis.ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions.GLUT3 is induced during epithelial-mesenchymal transition and promotes tumor cell proliferation in non-small cell lung cancer.ChIP-Seq: technical considerations for obtaining high-quality dataNuRD-mediated deacetylation of H3K27 facilitates recruitment of Polycomb Repressive Complex 2 to direct gene repression.Clustered ChIP-Seq-defined transcription factor binding sites and histone modifications map distinct classes of regulatory elements.Bivalent-like chromatin markers are predictive for transcription start site distribution in humanThe Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding.Cell-type specificity of ChIP-predicted transcription factor binding sitesNormalization of ChIP-seq data with control.A diffusion model for the coordination of DNA replication in Schizosaccharomyces pombe.Differential transcript isoform usage pre- and post-zygotic genome activation in zebrafishA computational model for histone mark propagation reproduces the distribution of heterochromatin in different human cell types.CENTDIST: discovery of co-associated factors by motif distribution.High-throughput sequencing reveals the disruption of methylation of imprinted gene in induced pluripotent stem cellsAP-2γ regulates oestrogen receptor-mediated long-range chromatin interaction and gene transcription.Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network.The ensembl regulatory buildIs this the right normalization? A diagnostic tool for ChIP-seq normalization.
P2860
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P2860
A signal-noise model for significance analysis of ChIP-seq with negative control.
description
2010 nî lūn-bûn
@nan
2010 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
A signal-noise model for significance analysis of ChIP-seq with negative control.
@ast
A signal-noise model for significance analysis of ChIP-seq with negative control.
@en
A signal-noise model for significance analysis of ChIP-seq with negative control.
@nl
type
label
A signal-noise model for significance analysis of ChIP-seq with negative control.
@ast
A signal-noise model for significance analysis of ChIP-seq with negative control.
@en
A signal-noise model for significance analysis of ChIP-seq with negative control.
@nl
prefLabel
A signal-noise model for significance analysis of ChIP-seq with negative control.
@ast
A signal-noise model for significance analysis of ChIP-seq with negative control.
@en
A signal-noise model for significance analysis of ChIP-seq with negative control.
@nl
P2093
P2860
P356
P1433
P1476
A signal-noise model for significance analysis of ChIP-seq with negative control.
@en
P2093
Chaopeng Ye
Chia-Lin Wei
Jianpeng Sheng
Lusy Handoko
Wing-Kin Sung
Xueliang Wei
P2860
P304
P356
10.1093/BIOINFORMATICS/BTQ128
P407
P577
2010-04-05T00:00:00Z