By Ferreira, J.; Correia, S.; Rocha, M.
Advances in Intelligent Systems and Computing
The liver is one of the largest organs of the adult body and most of its tissue is formed by hepatocyte cells, the main site of the metabolic conversions underlying its diverse physiological functions. Hepatocellular carcinoma is one of the most important human cancers. Genome-Scale Metabolic Models (GSMMs), mathematical representations of the cell metabolism in different organisms including humans, are useful tools to simulate metabolic phenotypes and understand metabolic diseases. In the last years, a few algorithms have been developed to generate tissue-specific metabolic models that allow the simulation of phenotypes for distinct cell types/tissues. This work based on general template GSMMs, which are integrated with available omics data. In this work, we propose to develop a pipeline for the systematic evaluation of these algorithms in the creation of models for regular hepatocytes and cancer cell lines, addressing the comparison of the final models obtained.