Journal article
Recon3D enables a three-dimensional view of gene variation in human metabolism
Technical University of Denmark1
University of Luxembourg2
University of California at San Diego3
University of Tübingen4
Chalmers University of Technology5
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark6
Yeast Cell Factories, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark7
Big Data 2 Knowledge, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark8
Network Reconstruction in Silico Biology, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark9
Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs.
Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism.
Recon3D is available at http://vmh.life.
Language: | English |
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Publisher: | Nature Publishing Group US |
Year: | 2018 |
Pages: | 272-281 |
Journal subtitle: | Science and Business of Biotechnology |
ISSN: | 15461696 and 10870156 |
Types: | Journal article |
DOI: | 10.1038/nbt.4072 |
ORCIDs: | 0000-0001-8578-8658 , 0000-0002-0430-6715 , 0000-0002-1240-5553 , 0000-0002-9031-9562 , 0000-0002-9476-4516 , 0000-0003-4903-9515 , 0000-0001-5346-9812 , 0000-0002-9955-6003 , 0000-0002-8071-7110 and Palsson, Bernhard O. |