Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/56416

TitleAnalysing algorithms and data sources for the tissue-specific reconstruction of liver healthy and cancer cells
Author(s)Ferreira, Jorge
Correia, Sara
Rocha, Miguel
KeywordsTissue-specific genome-scale metabolic models
Liver metabolism
Hepatocellular carcinoma
Issue dateMar-2017
PublisherSpringer Nature
JournalInterdisciplinary Sciences-Computational Life Sciences
CitationFerreira, Jorge; Correia, Sara; Rocha, Miguel, Analysing algorithms and data sources for the tissue-specific reconstruction of liver healthy and cancer cells. Interdisciplinary Sciences-Computational Life Sciences, 9(1), 36-45, 2017
Abstract(s)Genome-Scale Metabolic Models (GSMMs), mathematical representations of the cell metabolism in different organisms including humans, are resourceful tools to simulate metabolic phenotypes and understand associated diseases, such as obesity, diabetes and cancer. In the last years, different algorithms have been developed to generate tissue-specific metabolic models that simulate different phenotypes for distinct cell types. Hepatocyte cells are one of the main sites of metabolic conversions, mainly due to their diverse physiological functions. Most of the liver's tissue is formed by hepatocytes, being one of the largest and most important organs regarding its biological functions. Hepatocellular carcinoma is, also, one of the most important human cancers with high mortality rates. In this study, we will analyze four different algorithms (MBA, mCADRE, tINIT and FASTCORE) for tissue-specific model reconstruction, based on a template model and two types of data sources: transcriptomics and proteomics. These methods will be applied to the reconstruction of metabolic models for hepatocyte cells and HepG2 cancer cell line. The models will be analyzed and compared under different perspectives, emphasizing their functional analysis considering a set of metabolic liver tasks. The results show that there is no ``ideal'' algorithm. However, with the current analysis, we were able to retrieve knowledge about the metabolism of the liver.
TypeArticle
URIhttp://hdl.handle.net/1822/56416
DOI10.1007/s12539-017-0214-y
ISSN1913-2751
e-ISSN1867-1462
Publisher versionhttps://link.springer.com/journal/12539
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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