ChromaSig: a probabilistic approach to finding common chromatin signatures in the human genome.
about
Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic dataEvaluation of algorithm performance in ChIP-seq peak detectionUncovering correlated variability in epigenomic datasets using the Karhunen-Loeve transformGenomic views of STAT function in CD4+ T helper cell differentiationConstructing 3D interaction maps from 1D epigenomes.Integrating 5-hydroxymethylcytosine into the epigenomic landscape of human embryonic stem cellsThe Human Genome Project: big science transforms biology and medicineInterplay between chromatin state, regulator binding, and regulatory motifs in six human cell typesA tiered hidden Markov model characterizes multi-scale chromatin statesNext-generation genomics: an integrative approachDiscovery and characterization of chromatin states for systematic annotation of the human genomeChIP-seq: advantages and challenges of a maturing technologyMaster transcription factors and mediator establish super-enhancers at key cell identity genesCombinatorial epigenetic patterns as quantitative predictors of chromatin biology.Identification of biologically relevant enhancers in human erythroid cells.Predictive models of gene regulation from high-throughput epigenomics data.Spark: a navigational paradigm for genomic data explorationProbabilistic partitioning methods to find significant patterns in ChIP-Seq data.ClusTrack: feature extraction and similarity measures for clustering of genome-wide data setsDiscovery and annotation of functional chromatin signatures in the human genomeTranscription factor-associated combinatorial epigenetic pattern reveals higher transcriptional activity of TCF7L2-regulated intragenic enhancers.A nucleosomal approach to inferring causal relationships of histone modifications.Emerging roles of chromatin in the maintenance of genome organization and function in plants.Epigenetic domains found in mouse embryonic stem cells via a hidden Markov model.Discovering cooperative relationships of chromatin modifications in human T cells based on a proposed closeness measureseqMINER: an integrated ChIP-seq data interpretation platform.Next generation sequencing based approaches to epigenomics.A short survey of computational analysis methods in analysing ChIP-seq data.Distinct epigenomic landscapes of pluripotent and lineage-committed human cells.Discover regulatory DNA elements using chromatin signatures and artificial neural network.ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions.Efficiently identifying genome-wide changes with next-generation sequencing data.Computation for ChIP-seq and RNA-seq studiesThree-dimensional modeling of chromatin structure from interaction frequency data using Markov chain Monte Carlo sampling.Clustered ChIP-Seq-defined transcription factor binding sites and histone modifications map distinct classes of regulatory elements.CATCHprofiles: clustering and alignment tool for ChIP profiles.Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machines.A machine learning approach for identifying novel cell type-specific transcriptional regulators of myogenesis.Finding combinatorial histone code by semi-supervised biclusteringA global genome segmentation method for exploration of epigenetic patterns.
P2860
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P2860
ChromaSig: a probabilistic approach to finding common chromatin signatures in the human genome.
description
2008 nî lūn-bûn
@nan
2008 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@ast
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@en
type
label
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@ast
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@en
prefLabel
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@ast
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@en
P2093
P2860
P1476
ChromaSig: a probabilistic app ...... ignatures in the human genome.
@en
P2093
P2860
P304
P356
10.1371/JOURNAL.PCBI.1000201
P577
2008-10-17T00:00:00Z