Published December 16, 2019
| Version v3
Dataset
Open
Supplementary data and scripts for "An Atlas of Human Metabolism"
Creators
- Robinson, Jonathan L.1
- Kocabaş, Pınar1
- Wang, Hao1
- Cholley, Pierre-Etienne2
- Cook, Daniel1
- Nilsson, Avlant1
- Anton, Mihail2
- Ferreira, Raphael1
- Domenzain, Iván1
- Billa, Virinchi1
- Limeta, Angelo1
- Hedin, Alex1
- Gustafsson, Johan1
- Kerkhoven, Eduard J.1
- Svensson, L. Thomas2
- Palsson, Bernhard O.3
- Mardinoglu, Adil4
- Hansson, Lena5
- Uhlén, Mathias4
- Nielsen, Jens1
- 1. Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden
- 2. Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden
- 3. Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- 4. Department of Protein Science, Science for Life Laboratory, KTH–Royal Institute of Technology, Stockholm, Sweden
- 5. Novo Nordisk Research Centre Oxford, Oxford, UK
Description
This repository contains the models, data, and scripts associated with the publication "An Atlas of Human Metabolism".
The content is divided into three main directories, each containing their own README file containing instructions.
- tINIT_GEMs - Contains the genome-scale metabolic models (GEMs) generated in the study using the tINIT algorithm, as well as many scripts and datasets necessary to reproduce model generation, analyses, and figures.
- ec_GEMs - Contains the enzyme-constrained models (ecGEMs) generated in the study using the GECKO framework, as well as many scripts and datasets necessary to reproduce model generation, analyses, and figures.
- GEM_PRO - Contains the GEM-PRO dataframe with the protein structure information associated with the Human1 model.
Files
Human1_Publication_Data_Scripts.zip
Files
(1.6 GB)
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md5:0979f5571380c1ddcc754aa759e652fe
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Additional details
Funding
- Deciphering the coupled roles of protein secretion and metabolism in cancer using an integrative omics approach 5F32CA220848-02
- National Institutes of Health