This repository contains the current consensus genome-scale metabolic model of Saccharomyces cerevisiae. It is the continuation of the legacy project yeastnet. For the latest release please click here.
GEM Category: species; Utilisation: experimental data reconstruction, multi-omics integrative analysis, in silico strain design, model template; Field: metabolic-network reconstruction; Type of Model: reconstruction, curated; Model Source: YeastMetabolicNetwork; Omic Source: genomics, metabolomics; Taxonomy: Saccharomyces cerevisiae; Metabolic System: general metabolism; Bioreactor; Strain: S288C; Condition: aerobic, glucose-limited, defined media;
Last update: 2019-05-21
Main Model Descriptors:
|Saccharomyces cerevisiae||Yeast 7.6||3991||2691||1149|
This repository is administered by Benjamín J. Sánchez (@BenjaSanchez), Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology.
masterin the Github repo, or just download the latest release.
Make sure to load/save the model with the corresponding wrapper functions!
The model is available in
.xlsx (the last 2 extensions only in
master). Additionally, the following 2 files are available:
dependencies.txt: Tracks versions of toolboxes & SBML used for saving the model.
boundaryMets.txt: Contains a list of all boundary metabolites in model, listing the id and name.
missingFields: Folder with functions for adding missing fields to the model.
modelCuration: Folder with curation functions.
otherChanges: Folder with other types of changes.
increaseVersion.m: Updates the version of the model in
version.txtand as metaid in the
.xmlfile. Saves the model as
loadYeastModel.m: Loads the yeast model from the
.xmlfile for Matlab.
loadYeastModel.py: Loads the yeast model from the
.xmlfile for Python.
saveYeastModel.m: Saves yeast model as a
.txtfile, and updates
databases: Yeast data from different databases (KEGG, SGD, swissprot, etc).
modelCuration: Data files used for performing curations to the model. Mostly lists of new rxns, mets or genes added (or fixed) in the model.
physiology: Data on yeast growth under different conditions, biomass composition, gene essentiality experiments, etc.
Additionally, if you would like to cite the yeast-GEM project, you may also refer to the yeast 7 paper, and point to the new link in the text, e.g.: “The yeast consensus genome-scale model [Aung et al. 2013], which is currently being hosted at https://github.com/SysBioChalmers/yeast-GEM, […]”.
Finally, if you would like to cite the idea of hosting a genome-scale model in Github, you may also refer to the RAVEN 2 paper, which mentions this idea and exemplifies it on Streptomyces_coelicolor-GEM.
Contributions are always welcome! Please read the contributions guideline to get started.