A Systemic View of Target Identification: Modeling the Warburg Effect

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Abstract
The dynamics of the cell signaling network is highly regulated to adapt to temporal fluctuations and spatial heterogeneity of the microenvironment. Formal modeling of biological regulatory networks is an approach to identify which key components of this biological network, sometimes individual therapeutic targets, have a long-term influence on a disease-related phenotype of interest. We present an in silico formal screening strategy in the context of cancer metabolism to identify key hot spots in the metabolic network that could induce a systemic change of pathological cell phenotype such as the reversal of the Warburg effect.

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