Introduction

Diabesity has become a popular term to describe the specific form of diabetes that develops late in life and is associated with obesity. While there is a correlation between diabetes and obesity, the association is not universally predictive. Defining the metabolic characteristics of obesity that lead to diabetes, and how obese individuals who develop diabetes different from those who do not, are important goals. The use of large-scale omics analyses (e.g., metabolomic, proteomic, transcriptomic, and lipidomic) of diabetes and obesity may help to identify new targets to treat these conditions. This report discusses how various types of omics data can be integrated to shed light on the changes in metabolism that occur in obesity and diabetes.

Publications

  1. Application of combined omics platforms to accelerate biomedical discovery in diabesity.
    Cite this
    Kurland IJ, Accili D, Burant C, Fischer SM, Kahn BB, Newgard CB, Ramagiri S, Ronnett GV, Ryals JA, Sanders M, Shambaugh J, Shockcor J, Gross SS, 2013-05-01 - Annals of the New York Academy of Sciences

Credits

  1. Irwin J Kurland
    Developer

    Department of Medicine, Stable Isotope and Metabolomics Core Facility, United States of America

  2. Domenico Accili
    Developer

  3. Charles Burant
    Developer

  4. Steven M Fischer
    Developer

  5. Barbara B Kahn
    Developer

  6. Christopher B Newgard
    Developer

  7. Suma Ramagiri
    Developer

  8. Gabriele V Ronnett
    Developer

  9. John A Ryals
    Developer

  10. Mark Sanders
    Developer

  11. Joe Shambaugh
    Developer

  12. John Shockcor
    Developer

  13. Steven S Gross
    Investigator

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Summary
AccessionBT004234
Tool TypeApplication
Category
PlatformsWindows
Technologies
User InterfaceTerminal Command Line
Download Count0
Submitted BySteven S Gross