| Literature DB >> 32209698 |
Jonathan L Robinson1,2, Pınar Kocabaş1,2, Hao Wang1,3,4, Pierre-Etienne Cholley4, Daniel Cook1, Avlant Nilsson1, Mihail Anton4, Raphael Ferreira1, Iván Domenzain1,2, Virinchi Billa1, Angelo Limeta1, Alex Hedin1, Johan Gustafsson1,2, Eduard J Kerkhoven1, L Thomas Svensson4, Bernhard O Palsson5,6,7, Adil Mardinoglu8,9, Lena Hansson4,10, Mathias Uhlén5,8,11, Jens Nielsen12,2,5,13.
Abstract
Genome-scale metabolic models (GEMs) are valuable tools to study metabolism and provide a scaffold for the integrative analysis of omics data. Researchers have developed increasingly comprehensive human GEMs, but the disconnect among different model sources and versions impedes further progress. We therefore integrated and extensively curated the most recent human metabolic models to construct a consensus GEM, Human1. We demonstrated the versatility of Human1 through the generation and analysis of cell- and tissue-specific models using transcriptomic, proteomic, and kinetic data. We also present an accompanying web portal, Metabolic Atlas (https://www.metabolicatlas.org/), which facilitates further exploration and visualization of Human1 content. Human1 was created using a version-controlled, open-source model development framework to enable community-driven curation and refinement. This framework allows Human1 to be an evolving shared resource for future studies of human health and disease.Entities:
Year: 2020 PMID: 32209698 PMCID: PMC7331181 DOI: 10.1126/scisignal.aaz1482
Source DB: PubMed Journal: Sci Signal ISSN: 1945-0877 Impact factor: 8.192