refinegems

refineGEMs is a python package inteded to help with the curation of genome-scale metabolic models (GEMS).

https://github.com/draeger-lab/refinegems

Science Score: 75.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
Found CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
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DOI references
Found 4 DOI reference(s) in README
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Academic publication links
Links to: frontiersin.org, zenodo.org
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Institutional organization owner
Organization draeger-lab has institutional domain (uni-tuebingen.de)
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Scientific vocabulary similarity
Low similarity (15.5%) to scientific vocabulary

Last synced: 6 months ago · JSON representation ·

Repository

refineGEMs is a python package inteded to help with the curation of genome-scale metabolic models (GEMS).

Basic Info

Host: GitHub
Owner: draeger-lab
License: mit
Language: Python
Default Branch: main
Homepage: https://refinegems.readthedocs.io/en/latest/
Size: 80.5 MB

Statistics

Stars: 13
Watchers: 1
Forks: 2
Open Issues: 22
Releases: 16

Created almost 5 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

README.md

Python Version from PEP 621 TOML GitHub last commit (branch) Repo Size PyPI - Format

refineGEMs

refineGEMs is a python package intended to help with the curation of genome-scale metabolic models (GEMS).
⚠️🚧 DISCLAIMER: The documentation is currently under heavy-rework! The documentation can be found here.🚧

Overview
Installation
How to cite
Repositories using refineGEMs

Overview

Currently refineGEMs can be used for the investigation of a GEM, it can complete the following tasks:

loading GEMs with COBRApy and libSBML
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,

Installation

You can install refineGEMs via pip:

```bash pip install refineGEMs

```

or to a local conda environment where refineGEMs is distributed via this GitHub repository and all dependencies are denoted in the pyproject.toml file:

```bash

clone or pull the latest source code

git clone https://github.com/draeger-lab/refinegems.git cd refinegems

conda create -n python=3.10 (at least but < 3.13)

conda activate

check that pip comes from

which pip

pip install .

```

refineGEMs depends on the tools MCC and BOFdat which cannot directly be installed via PyPI or the pyproject.toml. Please install both tools before using refineGEMs:

```bash

For MCC, until hot fix is merged into main:

pip install "masschargecuration@git+https://github.com/Biomathsys/MassChargeCuration"

For BOFdat, our fork with hot fix(es):

pip install "bofdat@git+https://github.com/draeger-lab/BOFdat"

```

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.

Repositories using refineGEMs

CstriatumGEMs
draeger-lab/Shaemolyticus - private
draeger-lab/Ssanguinis - private

Owner

Name: Dräger Lab
Login: draeger-lab
Kind: organization
Email: andreas.draeger@uni-tuebingen.de
Location: Sand 14, 72076 Tübingen

Website: https://uni-tuebingen.de/en/127116
Twitter: DraegerLab
Repositories: 15
Profile: https://github.com/draeger-lab

Computational Systems Biology Lab within the Institute for Bioinformatics and Medical Informatics (IBMI) of the University of Tübingen

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use refineGEMs, please cite it as below."
authors:
- family-names: "Bäuerle"
  given-names: "Famke"
  orcid: "https://orcid.org/0000-0003-1387-0251"
- family-names: "Döbel"
  given-names: "Gwendolyn O."
  orcid: "https://orcid.org/0000-0002-8206-2576"
title: "refineGEMs"
version: 1.3.1
doi: 10.5281/zenodo.8270303 
date-released: 2023-10-30
url: "https://github.com/github-linguist/linguist"
preferred-citation:
  type: article
  authors:
  - family-names: "Bäuerle"
    given-names: "Famke"
    orcid: "https://orcid.org/0000-0003-1387-0251"
  - family-names: "Döbel"
    given-names: "Gwendolyn O."
    orcid: "https://orcid.org/0000-0002-8206-2576"
  - family-names: "Camus"
    given-names: "Laura"
    orcid: "https://orcid.org/0000-0003-1335-8901"
  - family-names: "Heilbronner"
    given-names: "Simon"
    orcid: "https://orcid.org/0000-0002-6774-2311"
  - family-names: "Dräger"
    given-names: "Andreas"
    orcid: "https://orcid.org/0000-0002-1240-5553"
  doi: "10.3389/fbinf.2023.1214074"
  journal: "Front. Bioinform."
  month: 10
  title: "Genome-scale metabolic models consistently predict in vitro characteristics of Corynebacterium striatum"
  issn: 2673-7647
  volume: 3
  year: 2023

GitHub Events

Total

Create event: 6
Issues event: 36
Release event: 3
Watch event: 3
Delete event: 4
Member event: 1
Issue comment event: 11
Push event: 187
Pull request review event: 1
Pull request event: 27
Fork event: 1

Last Year

Create event: 6
Issues event: 36
Release event: 3
Watch event: 3
Delete event: 4
Member event: 1
Issue comment event: 11
Push event: 187
Pull request review event: 1
Pull request event: 27
Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 20
Total pull requests: 3
Average time to close issues: 5 months
Average time to close pull requests: 30 days
Total issue authors: 3
Total pull request authors: 2
Average comments per issue: 0.9
Average comments per pull request: 0.0
Merged pull requests: 2
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 15
Pull requests: 3
Average time to close issues: 25 days
Average time to close pull requests: 30 days
Issue authors: 3
Pull request authors: 2
Average comments per issue: 0.27
Average comments per pull request: 0.0
Merged pull requests: 2
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

GwennyGit (17)
cb-Hades (14)
niinina (2)
famosab (1)

Pull Request Authors

GwennyGit (16)
cb-Hades (3)

Top Labels

Issue Labels

enhancement (27) refactoring (11) bug (7) documentation (5) help wanted (5) question (2)

Pull Request Labels

bug (13) documentation (12) enhancement (2)

Packages

Total packages: 1
Total downloads:
- pypi 29 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 16
Total maintainers: 3

pypi.org: refinegems

refineGEMs: a python package intended to help with the curation of genome-scale metabolic models (GEMS)

Documentation: https://refinegems.readthedocs.io/
License: MIT
Latest release: 1.5.0
published over 1 year ago

Versions: 16
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 29 Last month

Rankings

Dependent packages count: 10.1%

Dependent repos count: 21.6%

Average: 30.4%

Downloads: 59.5%

Maintainers (3)

famke.baeuerle g.o.gusak cb-Hades