about
Genome-wide epigenomic profiling for biomarker discoveryGenome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino AmericansApproaches for establishing the function of regulatory genetic variants involved in disease.Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Modelsfluff: exploratory analysis and visualization of high-throughput sequencing dataCell type-selective disease-association of genes under high regulatory load.Genetic and regulatory mechanism of susceptibility to high-hyperdiploid acute lymphoblastic leukaemia at 10p21.2.Rewiring of the inferred protein interactome during blood development studied with the tool PPICompare.Statistical methods for detecting differentially methylated loci and regionsScreening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)Biological embedding of early-life exposures and disease risk in humans: a role for DNA methylation.Bioinformatics Pipeline for Transcriptome Sequencing Analysis.Improving understanding of chromatin regulatory proteins and potential implications for drug discovery.Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study.RegulatorTrail: a web service for the identification of key transcriptional regulators.The genetics revolution in rheumatology: large scale genomic arrays and genetic mapping.Differential peak calling of ChIP-seq signals with replicates with THORDetecting differential peaks in ChIP-seq signals with ODIN.Epigenetic epidemiology as a tool to understand the role of immunity in chronic disease.The non-coding RNA landscape of human hematopoiesis and leukemia.Epigenetic changes in T-cell and monocyte signatures and production of neurotoxic cytokines in ALS patients.Epigenetic programming of monocyte-to-macrophage differentiation and trained innate immunity.BAT: Bisulfite Analysis Toolkit: BAT is a toolkit to analyze DNA methylation sequencing data accurately and reproducibly. It covers standard processing and analysis steps from raw read mapping up to annotation data integration and calculation of corExpression Atlas: gene and protein expression across multiple studies and organisms.Thinking BIG rheumatology: how to make functional genomics data work for you.Common α-globin variants modify hematologic and other clinical phenotypes in sickle cell trait and disease.Epigenome-wide association in adipose tissue from the METSIM cohort.[The European Blueprint project: towards a full epigenome characterization of the immune system].ChromTime: modeling spatio-temporal dynamics of chromatin marksAutosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivationNegative Evidence for a Functional Role of Neuronal DNMT3a in Persistent Pain
P2860
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P2860
description
2013 nî lūn-bûn
@nan
2013 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
BLUEPRINT: mapping human blood cell epigenomes
@ast
BLUEPRINT: mapping human blood cell epigenomes
@en
BLUEPRINT: mapping human blood cell epigenomes
@nl
type
label
BLUEPRINT: mapping human blood cell epigenomes
@ast
BLUEPRINT: mapping human blood cell epigenomes
@en
BLUEPRINT: mapping human blood cell epigenomes
@nl
prefLabel
BLUEPRINT: mapping human blood cell epigenomes
@ast
BLUEPRINT: mapping human blood cell epigenomes
@en
BLUEPRINT: mapping human blood cell epigenomes
@nl
P2860
P3181
P1433
P1476
BLUEPRINT: mapping human blood cell epigenomes
@en
P2093
Hendrik G Stunnenberg
P2860
P304
P3181
P356
10.3324/HAEMATOL.2013.094243
P407
P577
2013-10-01T00:00:00Z