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Systems biology for identifying liver toxicity pathways

Drug-induced liver toxicity is one of the leading causes of acute liver failure in the United States, exceeding all other causes combined. The objective of this paper is to describe systems biology methods for identifying pathways involved in liver toxicity induced by free fatty acids (FFA) and tumo...

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Detalles Bibliográficos
Autores principales: Li, Zheng, Chan, Christina
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2654485/
https://www.ncbi.nlm.nih.gov/pubmed/19278558
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author Li, Zheng
Chan, Christina
author_facet Li, Zheng
Chan, Christina
author_sort Li, Zheng
collection PubMed
description Drug-induced liver toxicity is one of the leading causes of acute liver failure in the United States, exceeding all other causes combined. The objective of this paper is to describe systems biology methods for identifying pathways involved in liver toxicity induced by free fatty acids (FFA) and tumor necrosis factor (TNF)-α in human hepatoblastoma cells (HepG2/C3A). Systems biology approaches were developed to integrate multi-level data, i.e., gene expression, metabolite profile, toxicity measurements and a priori knowledge to identify gene targets for modulating liver toxicity. Targets that modulate liver toxicity, in vitro, were computationally predicted and some targets were experimentally validated.
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spelling pubmed-26544852009-03-13 Systems biology for identifying liver toxicity pathways Li, Zheng Chan, Christina BMC Proc Proceedings Drug-induced liver toxicity is one of the leading causes of acute liver failure in the United States, exceeding all other causes combined. The objective of this paper is to describe systems biology methods for identifying pathways involved in liver toxicity induced by free fatty acids (FFA) and tumor necrosis factor (TNF)-α in human hepatoblastoma cells (HepG2/C3A). Systems biology approaches were developed to integrate multi-level data, i.e., gene expression, metabolite profile, toxicity measurements and a priori knowledge to identify gene targets for modulating liver toxicity. Targets that modulate liver toxicity, in vitro, were computationally predicted and some targets were experimentally validated. BioMed Central 2009-03-10 /pmc/articles/PMC2654485/ /pubmed/19278558 Text en Copyright © 2009 Li and Chan; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Li, Zheng
Chan, Christina
Systems biology for identifying liver toxicity pathways
title Systems biology for identifying liver toxicity pathways
title_full Systems biology for identifying liver toxicity pathways
title_fullStr Systems biology for identifying liver toxicity pathways
title_full_unstemmed Systems biology for identifying liver toxicity pathways
title_short Systems biology for identifying liver toxicity pathways
title_sort systems biology for identifying liver toxicity pathways
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2654485/
https://www.ncbi.nlm.nih.gov/pubmed/19278558
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