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Analyzing omics data of biological samples

In the projects I participated in the VirtualLiver Network, chip array experiments were performed, mostly on the Affymetrix platform to obtain mRNA transcript profiles. As the final aim of VirtualLiver are multi-scale modeling, these experiments served as a resource to identify genes whose expression is affect by the various tretments of interest. These treatments are
  • tested on cell culture of primary cell cultures:
    • cytokines occurring during liver regeneration. HGF, IL6, TGFβ, TNFα tested
    • cytokines occurring during liver inflammation. TGFβ
    • agonists of the nuclear receptors PXR, CAR, PPARα which are triggered in liver intoxication and also in liver development
  • tested on mouse liver tissue material:
    • fractioned periportal vs. pericentral hepatocytes
    • genetically modified mouse with altered Hedgehog signaling
  • different stages of obesity, steatosis, and stetohepatitis obtained from human liver biopsies
The analyses are:
  • ANOVA and t-test to assess the singnificance of the changes
  • ModeScore analysis to assert which metabolic functions are affected
  • Show the most changed genes, for the assumption that the amplitude of change corresponds roughly to the importance of the process
  • Show the most changed genes in each of the gene classes
  • Assert synergy, attenuation, divergence, and dominance in the co-treatment of several factors