Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN

The complexity of genome-scale metabolic networks (GEMs) hinders their application in specific physiological contexts. Here, the authors introduce a framework to reduce thermodynamically curated GEMs to the subnetworks of interest and demonstrate its application by deriving leukemia-specific models.

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Autores principales:	Maria Masid, Meric Ataman, Vassily Hatzimanikatis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/3d41aec2fe0240f39f36e6ac9ec3d22c
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spelling	oai:doaj.org-article:3d41aec2fe0240f39f36e6ac9ec3d22c2021-12-02T15:02:30ZAnalysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN10.1038/s41467-020-16549-22041-1723https://doaj.org/article/3d41aec2fe0240f39f36e6ac9ec3d22c2020-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-16549-2https://doaj.org/toc/2041-1723The complexity of genome-scale metabolic networks (GEMs) hinders their application in specific physiological contexts. Here, the authors introduce a framework to reduce thermodynamically curated GEMs to the subnetworks of interest and demonstrate its application by deriving leukemia-specific models.Maria MasidMeric AtamanVassily HatzimanikatisNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-12 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Maria Masid Meric Ataman Vassily Hatzimanikatis Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN
description	The complexity of genome-scale metabolic networks (GEMs) hinders their application in specific physiological contexts. Here, the authors introduce a framework to reduce thermodynamically curated GEMs to the subnetworks of interest and demonstrate its application by deriving leukemia-specific models.
format	article
author	Maria Masid Meric Ataman Vassily Hatzimanikatis
author_facet	Maria Masid Meric Ataman Vassily Hatzimanikatis
author_sort	Maria Masid
title	Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN
title_short	Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN
title_full	Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN
title_fullStr	Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN
title_full_unstemmed	Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN
title_sort	analysis of human metabolism by reducing the complexity of the genome-scale models using redhuman
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/3d41aec2fe0240f39f36e6ac9ec3d22c
work_keys_str_mv	AT mariamasid analysisofhumanmetabolismbyreducingthecomplexityofthegenomescalemodelsusingredhuman AT mericataman analysisofhumanmetabolismbyreducingthecomplexityofthegenomescalemodelsusingredhuman AT vassilyhatzimanikatis analysisofhumanmetabolismbyreducingthecomplexityofthegenomescalemodelsusingredhuman
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Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN

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