Welcome to refineGEMs!
refineGEMs
is a Python package intended
to help with the curation of genome-scale metabolic models (GEMS).
Hint
For bug reports please write issues on the GitHub page or open a discussion here.
Overview
Currently refineGEMs
can be used for the investigation of a GEM, it can complete the following tasks:
loading GEMs with
COBRApy
andlibSBML
report number of metabolites, reactions and genes
report orphaned, deadends and disconnected metabolites
report mass and charge unbalanced reactions
report Memote score
compare the genes present in the model to the genes found in: * the KEGG Database (Note: This requires the GFF file and the KEGG identifier of your organism.) * Or the BioCyc Database (Note: This requires that a database entry for your organism exists in BioCyc.)
compare the charges and masses of the metabolites present in the model to the charges and masses denoted in the ModelSEED Database.
Other applications of refineGEMs
to curate a given model include:
The correction of a model created with CarveMe v1.5.1 or v1.5.2 (for example moving all relevant information from the notes to the annotation field or automatically annotating the GeneProduct section of the model with the respective NCBI gene/protein identifiers from the GeneProduct identifiers),
The addition of KEGG Pathways as Groups (using the libSBML Groups Plugin),
Updating the SBO-Term annotations based on SBOannotator[1],
Updating the annotation of metabolites and extending the model with reactions (for the purpose of filling gaps) based on a table filled by the user
data/manual_annotations.xlsx
(Note: This only works when the structure of the example Excel file is used.),And extending the model with all information surrounding reactions including the corresponding GeneProducts and metabolites by filling in the table
data/modelName_gapfill_analysis_date_example.xlsx
(Note: This also only works when the structure of the example Excel file is used).
How to cite
When using refineGEMs, please cite the latest publication:
Famke Bäuerle, Gwendolyn O. Döbel, Laura Camus, Simon Heilbronner, and Andreas Dräger. Genome-scale metabolic models consistently predict in vitro characteristics of Corynebacterium striatum. Front. Bioinform., oct 2023. doi:10.3389/fbinf.2023.1214074.
- Installation
- Usage
- Main modules
- From laboratory to in silico medium
- API access
- refineGEMs.biomass module
- refineGEMs.charges module
- refineGEMs.comparison module
- refineGEMs.curate module
- refineGEMs.cvterms module
- refineGEMs.gapfill module
- refineGEMs.growth module
- refineGEMs.investigate module
- refineGEMs.io module
- refineGEMs.modelseed module
- refineGEMs.pathways module
- refineGEMs.polish module
- refineGEMs.sboann module
- Pipeline: From genome sequence to draft model
- Notes for developers