Published November 28, 2021
| Version 1
Dataset
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Prediction of metabolites associated with somatic mutations in cancers
Authors/Creators
- 1. KAIST
- 2. Seoul National University Hospital
Description
- GEMs_PCAWG: 943 cancer patient-specific genome-scale metabolic models (GEMs) for 24 different cancer types reconstructed using the Pan-Cancer Analysis of Whole Genomes (PCAWG) RNA-seq data and generic human GEM 'Recon 2M.2'
- GEMs_AML: 16 acute myeloid leukemia (AML) patient-specific GEMs reconstructed using their corresponding RNA-seq data and Recon 2M.2
Notes
This study was supported by the Project of Promoting Inclusive Growth through Artificial Intelligence and Blockchain Technology and Diffusion of Precision Medicine (1711125351) funded by the Ministry of Science and ICT through KAIST's Korea Policy Center for the Fourth Industrial Revolution. This work was also supported by the KAIST Cross-Generation Collaborative Lab project of the Ministry of Science and ICT through the National Research Foundation of Korea, and by Kwon Oh-Hyun Assistant Professor fund of the KAIST Development Foundation.
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