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This repository contains the genome-scale metabolic model (GEM) of the thraustochytridAurantiochytrium sp. T66. Considerably improving on the model quality and scope to that of previously published thraustochytrid GEMs, this model provides a great starting point for conducting research on thraustochytrids as microbial cell factories.

If you use T66-GEM please cite the following paper:

Simensen, V., Voigt, A., Almaas, E. High-quality genome-scale metabolic model of Aurantiochytrium sp. T66. Biotechnology and Bioengineering, 118:2105–2117 (2021)doi:10.1002/bit.27726

Utilisation: model template;in silico strain design; multi-omics integrative analysis
Field: metabolic-network reconstruction
Type of model: reconstruction; curated
Model source:iVS1191
Omic source: genomics; transcriptomics; metabolomics
Taxonomic name:Aurantiochytrium sp. T66
Taxonomy ID:taxonomy:1749249
Genome ID:insdc.gca:GCA_001462505.1
Metabolic system: general metabolism
Condition: aerobic; glucose-limited; defined media

If you want to use the model, any software that accepts SBML L3V1 FBCv3 formatted model files will work. We recommend the following as they are well-maintained and used by most researchers in the constraint-based metabolic modeling community:

• MATLAB
  • COBRA Toolbox andRAVEN Toolbox
• Python
  • cobrapy

The following code shows how the model can be read and written:

• In Matlab using either COBRA or RAVEN:

  cd./code% For RAVEN use cobra = falsecobra=true;model= loadT66Model(cobra);% loadingsaveT66Model(model);% saving

• In Python using cobrapy:

  frommodel_ioimportread_t66_model,write_t66_modelmodel=read_t66_model()# loadingwrite_t66_model(model)# saving

Contributions are always welcome! Please read thecontributing guideline to get started.

Code contributors are reported automatically by GitHub underContributors, while other contributions come in asIssues.