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Primary hepatocytes were exposed to a stimulus by exchanging culture medium, thereby simulating changes in the blood composition. The expression of genes at different time points was recorded. Differentially expressed genes were clustered using fuzzy c-means algorithm into five groups. The arcs of the possible network were identified using the NetGenerator algorithm under the restriction of biological knowledge. The analysis was restricted to the main metabolic pathways of hepatocytes. The reverse
Dynamic optimization model to study control points in metabolic pathways to identify general strategies behind pathway regulation.
Toxic intermediates determine which enzyme control pathway flux and prevent their accumulation.
Therefore those enzymes are drug targets since deregulation leads to self-poisoning of pathogens.