Computational Biology of Diabetes

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

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  • 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
  • Impact of food & nutrition in diabetes management
  • Impact of physical activity & yoga therapy

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Computational Biology of Diabetes Conference Speakers

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