Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome. - Wikidata - wikimedia - TriplyDB

Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.

Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.

http://www.wikidata.org/entity/Q33382893

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When is hub gene selection better than standard meta-analysis?WGCNA: an R package for weighted correlation network analysis Network biomarkers reveal dysfunctional gene regulations during disease progression Genetic, transcriptomic, and epigenetic studies of HIV-associated neurocognitive disorder Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers Systems analysis of human brain gene expression: mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer's disease Systems genetics: a novel approach to dissect the genetic basis of osteoporosis.A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.Causal inference of gene regulation with subnetwork assembly from genetical genomics data.FUMET: a fuzzy network module extraction technique for gene expression data.Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells.Network module detection: Affinity search technique with the multi-node topological overlap measure.A systems genetics approach implicates USF1, FADS3, and other causal candidate genes for familial combined hyperlipidemia.Inferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks.A general co-expression network-based approach to gene expression analysis: comparison and applications.Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse.Is human blood a good surrogate for brain tissue in transcriptional studies?An inference method from multi-layered structure of biomedical data Coexpression network analysis of neural tissue reveals perturbations in developmental processes in schizophrenia.Assessment of a 44 gene classifier for the evaluation of chronic fatigue syndrome from peripheral blood mononuclear cell gene expression.DNA methylation modifications associated with chronic fatigue syndrome.Human gene correlation analysis (HGCA): a tool for the identification of transcriptionally co-expressed genes.PPAR agonists regulate brain gene expression: relationship to their effects on ethanol consumption Gene network modular-based classification of microarray samples.Identification of pathway deregulation--gene expression based analysis of consistent signal transduction.Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects.Hope for GWAS: relevant risk genes uncovered from GWAS statistical noise.Modules, networks and systems medicine for understanding disease and aiding diagnosis.Systems biology with high-throughput sequencing reveals genetic mechanisms underlying the metabolic syndrome in the Lyon hypertensive rat.Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis.Gender-specific cytokine pathways, targets, and biomarkers for the switch from health to adenoma and colorectal cancer.A systems genetic analysis of high density lipoprotein metabolism and network preservation across mouse models.Integrating mRNA and miRNA Weighted Gene Co-Expression Networks with eQTLs in the Nucleus Accumbens of Subjects with Alcohol Dependence.Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis.Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs.Epigenetic modifications and glucocorticoid sensitivity in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).The aetiopathogenesis of fatigue: unpredictable, complex and persistent Alternative α-synuclein transcript usage as a convergent mechanism in Parkinson's disease pathology.The Association Between Low Back Pain and Composition of IgG Glycome Investigating the Combinatory Effects of Biological Networks on Gene Co-expression.

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P2860

Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.

http://www.wikidata.org/entity/Q33382893

description

2008 nî lūn-bûn

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2008 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

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2008 թվականի նոյեմբերին հրատարակված գիտական հոդված

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2008年の論文

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name

Integrated weighted gene co-ex ...... n to chronic fatigue syndrome.

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Integrated weighted gene co-ex ...... n to chronic fatigue syndrome.

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Integrated weighted gene co-ex ...... n to chronic fatigue syndrome.

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Integrated weighted gene co-ex ...... n to chronic fatigue syndrome.

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Integrated weighted gene co-ex ...... n to chronic fatigue syndrome.

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Integrated weighted gene co-ex ...... n to chronic fatigue syndrome.

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Angela P Presson

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Charlyn J Suarez

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Jeanette C Papp

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Mangalathu S Rajeevan

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Steve Horvath

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Toni Whistler

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P2860

Geometric interpretation of gene coexpression network analysis

Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution

'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

The c-Myc target gene PRDX3 is required for mitochondrial homeostasis and neoplastic transformation

Deficiency of the ADP-forming succinyl-CoA synthase activity is associated with encephalomyopathy and mitochondrial DNA depletion

Immune modulation of the hypothalamic-pituitary-adrenal (HPA) axis during viral infection

Chronic fatigue syndrome--a clinically empirical approach to its definition and study

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Integration of gene expression, clinical, and epidemiologic data to characterize Chronic Fatigue Syndrome

Variations in DNA elucidate molecular networks that cause disease

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Suzanne D. Vernon

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