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.
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2020-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-020-16549-2 |
| Summary: | 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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| ISSN: | 2041-1723 |