Systems biology approach reveals genome to phenome correlation in type 2 diabetes - Wikidata - thesis-toulmin - TriplyDB

Systems biology approach reveals genome to phenome correlation in type 2 diabetes

Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease.The pancreatic β-cell transcriptome and integrated-omics.Biobanking across the phenome - at the center of chronic disease research Inflammation, metaflammation and immunometabolic disorders.Network Cluster Analysis of Protein-Protein Interaction Network-Identified Biomarker for Type 2 Diabetes.Novel Observations From Next-Generation RNA Sequencing of Highly Purified Human Adult and Fetal Islet Cell Subsets.Prediction of scaffold proteins based on protein interaction and domain architectures Subpathway-GMir: identifying miRNA-mediated metabolic subpathways by integrating condition-specific genes, microRNAs, and pathway topologies Perspective: a systems approach to diabetes research.Cellular Signaling Pathways in Insulin Resistance-Systems Biology Analyses of Microarray Dataset Reveals New Drug Target Gene Signatures of Type 2 Diabetes Mellitus.Serum microRNA profiling and bioinformatics analysis of patients with type 2 diabetes mellitus in a Chinese population Epistatic effects of multiple receptor genes on pathophysiology of asthma - its limits and potential for clinical application.Computational analyses of type 2 diabetes-associated loci identified by genome-wide association studies.

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

http://www.wikidata.org/entity/Q28484866

description

2013 nî lūn-bûn

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2013 թուականին հրատարակուած գիտական յօդուած

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2013年の論文

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Systems biology approach reveals genome to phenome correlation in type 2 diabetes

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Ashok Kumar Mathur

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Dinesh Jindel

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Malabika Datta

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Priyanka Jain

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Sandeep Kumar Mathur

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Saurabh Vig

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P2860

Potential etiologic and functional implications of genome-wide association loci for human diseases and traits

Data-driven integration of epidemiological and toxicological data to select candidate interacting genes and environmental factors in association with disease

Functional proteomics mapping of a human signaling pathway

Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis

Five years of GWAS discovery

Smad3 deficiency in mice protects against insulin resistance and obesity induced by a high-fat diet

mTOR signaling in growth control and disease

Osprey: a network visualization system

Handling multiple testing while interpreting microarrays with the Gene Ontology Database

Metabolomics in diabetes research

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type-2 diabetes

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