Strategies for aggregating gene expression data: the collapseRows R function.
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When is hub gene selection better than standard meta-analysis?DNA methylation age of human tissues and cell typesEfficient and biologically relevant consensus strategy for Parkinson's disease gene prioritization.N17 Modifies mutant Huntingtin nuclear pathogenesis and severity of disease in HD BAC transgenic miceIdentification of Chemical Inhibitors of β-Catenin-Driven Liver Tumorigenesis in ZebrafishRiboTag analysis of actively translated mRNAs in Sertoli and Leydig cells in vivo.Assessing Concordance of Drug-Induced Transcriptional Response in Rodent Liver and Cultured HepatocytesSystems analysis of human brain gene expression: mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer's diseaseDistinct neurogenomic states in basal ganglia subregions relate differently to singing behavior in songbirds.Overrepresentation of glutamate signaling in Alzheimer's disease: network-based pathway enrichment using meta-analysis of genome-wide association studies.A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastomaRhoC Is an Unexpected Target of RhoGDI2 in Prevention of Lung Colonization of Bladder Cancer.Long-term neural and physiological phenotyping of a single humanGlia Open Access Database (GOAD): A comprehensive gene expression encyclopedia of glia cells in health and disease.Comparison and evaluation of pathway-level aggregation methods of gene expression data.curatedOvarianData: clinically annotated data for the ovarian cancer transcriptomeImproving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.Head and neck cancer subtypes with biological and clinical relevance: Meta-analysis of gene-expression data.Co-expression network analysis and genetic algorithms for gene prioritization in preeclampsiaAn additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.Co-expression network analysis identifies Spleen Tyrosine Kinase (SYK) as a candidate oncogenic driver in a subset of small-cell lung cancerAssociating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis.Long noncoding RNA expression signature to predict platinum-based chemotherapeutic sensitivity of ovarian cancer patients.Aging effects on DNA methylation modules in human brain and blood tissue.Cross-study validation for the assessment of prediction algorithms.Transcriptional Network Analysis Reveals Drought Resistance Mechanisms of AP2/ERF Transgenic Rice.Transcriptional landscape of the prenatal human brainAn integrated genomic and metabolomic framework for cell wall biology in rice.Characterization of functional reprogramming during osteoclast development using quantitative proteomics and mRNA profiling.Aerobic glycolysis in the human brain is associated with development and neotenous gene expressionA common gene expression signature in Huntington's disease patient brain regions.Adipose co-expression networks across Finns and Mexicans identify novel triglyceride-associated genes.Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels.Conserved molecular signatures of neurogenesis in the hippocampal subgranular zone of rodents and primates.Glioma-associated microglia/macrophages display an expression profile different from M1 and M2 polarization and highly express Gpnmb and Spp1.A cell of origin gene signature indicates human bladder cancer has distinct cellular progenitors.Differential induction of TLR3-dependent innate immune signaling by closely related parasite species.Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemiaPervasive and opposing effects of Unpredictable Chronic Mild Stress (UCMS) on hippocampal gene expression in BALB/cJ and C57BL/6J mouse strainsSeasonal effects on gene expression.
P2860
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P2860
Strategies for aggregating gene expression data: the collapseRows R function.
description
2011 nî lūn-bûn
@nan
2011 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Strategies for aggregating gene expression data: the collapseRows R function.
@ast
Strategies for aggregating gene expression data: the collapseRows R function.
@en
type
label
Strategies for aggregating gene expression data: the collapseRows R function.
@ast
Strategies for aggregating gene expression data: the collapseRows R function.
@en
prefLabel
Strategies for aggregating gene expression data: the collapseRows R function.
@ast
Strategies for aggregating gene expression data: the collapseRows R function.
@en
P2093
P2860
P356
P1433
P1476
Strategies for aggregating gene expression data: the collapseRows R function.
@en
P2093
Chaochao Cai
Daniel R Salomon
Jeremy A Miller
Peter Langfelder
Steve Horvath
P2860
P2888
P356
10.1186/1471-2105-12-322
P577
2011-08-04T00:00:00Z
P5875
P6179
1013163514