Integrative network analysis reveals molecular mechanisms of blood pressure regulation - Wikidata - awgldk - TriplyDB

Integrative network analysis reveals molecular mechanisms of blood pressure regulation

Integrative network analysis reveals molecular mechanisms of blood pressure regulation

http://www.wikidata.org/entity/Q35577186

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Systems Medicine as an Emerging Tool for Cardiovascular Genetics Integrating GWAS and Co-expression Network Data Identifies Bone Mineral Density Genes SPTBN1 and MARK3 and an Osteoblast Functional Module.Using GWAS to identify novel therapeutic targets for osteoporosis.A Systems Genetics Approach Identified GPD1L and its Molecular Mechanism for Obesity in Human Adipose Tissue.Joint analysis of multiple phenotypes: summary of results and discussions from the Genetic Analysis Workshop 19.Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies.Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension.Exploring the molecular basis of age-related disease comorbidities using a multi-omics graphical model.Cohort Profile: The Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology.Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease.Linking inflammation and hypertension via LNK/SH2B3.Transcriptome-Wide Analysis Identifies Novel Associations With Blood Pressure.Building on a Legacy of Hypertension Research: Charting Our Future Together.Dendritic cells and isolevuglandins in immunity, inflammation, and hypertension.Sigma 2 Receptor/Tmem97 Agonists Produce Long Lasting Antineuropathic Pain Effects in Mice.Genetic Epidemiology and Public Health: The Evolution From Theory to Technology.Role of Axl in T-Lymphocyte Survival in Salt-Dependent Hypertension.Towards Precision Medicine for Hypertension: A Review of Genomic, Epigenomic, and Microbiomic Effects on Blood Pressure in Experimental Rat Models and Humans.DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation.Prediction and Subtyping of Hypertension from Pan-Tissue Transcriptomic and Genetic Analyses.A Two-Stage Whole-Genome Gene Expression Association Study of Young-Onset Hypertension in Han Chinese Population of Taiwan.Growing old, yet staying young: The role of telomeres in bats' exceptional longevity.New perspectives: systems medicine in cardiovascular disease.KDiamend: a package for detecting key drivers in a molecular ecological network of disease.Comprehensive innate immune profiling of chikungunya virus infection in pediatric cases Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach

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Integrative network analysis reveals molecular mechanisms of blood pressure regulation

http://www.wikidata.org/entity/Q35577186

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2015 nî lūn-bûn

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2015年の論文

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2015年論文

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2015年論文

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2015年論文

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2015年論文

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2015年論文

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2015年论文

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2015年论文

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2015年论文

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name

Integrative network analysis reveals molecular mechanisms of blood pressure regulation

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Integrative network analysis reveals molecular mechanisms of blood pressure regulation

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Integrative network analysis reveals molecular mechanisms of blood pressure regulation

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Integrative network analysis reveals molecular mechanisms of blood pressure regulation

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Molecular Systems Biology

P1476

Integrative network analysis reveals molecular mechanisms of blood pressure regulation

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P2093

Andrew D Johnson

http://www.w3.org/2001/XMLSchema#string

Bin Zhang

http://www.w3.org/2001/XMLSchema#string

Brian H Chen

http://www.w3.org/2001/XMLSchema#string

Christopher J O'Donnell

http://www.w3.org/2001/XMLSchema#string

Daniel Levy

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David G Harrison

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International Consortium for Blood Pressure GWAS (ICBP)

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Jun Zhu

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Nalini Raghavachari

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Paul Courchesne

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P2860

WGCNA: an R package for weighted correlation network analysis

Gene ontology: tool for the unification of biology

Gene Expression Signatures of Coronary Heart Disease

Variations in DNA elucidate molecular networks that cause disease

Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk

MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes

TopHat: discovering splice junctions with RNA-Seq

The human disease network

Statistical significance for genomewide studies

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10.15252/MSB.20145399

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1

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11

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Ramachandran S. Vasan

Mohamed A Saleh

Allison E Norlander

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2015-01-01T00:00:00Z

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275103126

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25882670

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