Abstract
Metabolism is the process by which cells and organisms obtain nutrients and energy to perform their functions. In the last years, many human diseases, including cancer, diabetes, and cardiac diseases, have been associated with altered metabolism. Understanding these metabolic alterations at a systems level will help to design better therapies and treatments. In this context, the human genome-scale metabolic models (GEMs) combined with mathematical methods and experimental data have been powerful tools to investigate cellular metabolism under different conditions. Here, we review current methods and models to study human metabolism, and we discuss future perspectives, including a community call for an agreement on how to use GEMs in a context-specific manner for quantitative analysis of human metabolism.
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