Computational Biology of Diabetes

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications

  • Computational approach to chemical etiologies of diabetes
  • Computational disease gene identification
  • Model construction processes for survival prediction
  • Computational Methods for the Early Detection of Diabetes
  • Computational techniques to uncover the etiology of disease
  • Innovative Bioinformatic methods for Diabetes

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5th World Summit on Diabetes Expo

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3rd International Summit on Hormonal Disorders

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20th World Congress on Endocrinology & Diabetes

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