meneco

:m: Metabolic network completion

https://github.com/bioasp/meneco

Science Score: 23.0%

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

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  • codemeta.json file
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  • DOI references
    Found 12 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    3 of 9 committers (33.3%) from academic institutions
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    Low similarity (11.2%) to scientific vocabulary

Keywords

metabolic-pathways metabolic-reconstruction
Last synced: 11 months ago · JSON representation

Repository

:m: Metabolic network completion

Basic Info
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  • Stars: 9
  • Watchers: 9
  • Forks: 9
  • Open Issues: 5
  • Releases: 9
Topics
metabolic-pathways metabolic-reconstruction
Created over 12 years ago · Last pushed over 3 years ago
Metadata Files
Readme Changelog License

README.md

Meneco PyPI version

Installation

Requires Python >= 3.7

Required packages (starting from version 2.0 of the package):

You can install Meneco by running:

sh python setup.py install

You should always use a virtual environment (virtualenv, virtualenv wrapper) when using Python

Usage from console

Typical usage is:

sh meneco -d draftnetwork.sbml -s seeds.sbml -t targets.sbml -r repairnetwork.sbml

For more options you can ask for help as follows:

```text usage: meneco [-h] -d DRAFTNET -s SEEDS -t TARGETS [-r REPAIRNET] [--enumerate] [--json]

optional arguments: -h, --help show this help message and exit -d DRAFTNET, --draftnet DRAFTNET metabolic network in SBML format -s SEEDS, --seeds SEEDS seeds in SBML format -t TARGETS, --targets TARGETS targets in SBML format -r REPAIRNET, --repairnet REPAIRNET perform network completion using REPAIRNET a metabolic network in SBML format --enumerate enumerate all minimal completions --json produce JSON output ```

Calling Meneco from a python script

You can use Meneco from python by calling the command run_meneco() with the paths of files as input arguments and a boolean value for the enumeration (True for the enumeration, else False) :

```py from meneco import run_meneco

result = run_meneco(draftnet="toy/draft.sbml", seeds="toy/seeds.sbml", targets="toy/targets.sbml", repairnet="toy/repair.sbml", enumeration=False, json=True) ```

The output will be the set of unproducible targets, reconstructable targets, a dictionnary of essentials reactions for each target, one minimal solution, the set of reactions belonging to the intersection of solutions, the set of reactions belonging to the union of solutions and a list of lists corresponding to the reactions for each solution (if enumeration == True).

For a step by step demonstration on how to use Meneco as a library, have a look at our notebooks here or here.

Bibliography

Please cite the following paper when using Meneco:

S. Prigent et al., “Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks,” PLOS Computational Biology, vol. 13, no. 1, p. e1005276, Jan. 2017. https://doi.org/10.1371/journal.pcbi.1005276

The concepts underlying Meneco is described in this paper:

T. Schaub and S. Thiele, “Metabolic network expansion with answer set programming,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, vol. 5649 LNCS, pp. 312–326. https://doi.org/10.1007/978-3-642-02846-5_27

A first application of the method was presented in:

G. Collet et al., “Extending the Metabolic Network of Ectocarpus Siliculosus Using Answer Set Programming,” in LPNMR 2013: Logic Programming and Nonmonotonic Reasoning, 2013, pp. 245–256. https://doi.org/10.1007/978-3-642-40564-8_25

Samples

Sample files for the reconstruction of Ectocarpus are available here: ectocyc.sbml, metacyc_16-5.sbml, seeds.sbml, targets.sbml

Owner

  • Name: BioASP
  • Login: bioasp
  • Kind: organization
  • Email: bioasp@gmail.com

ASP-based software for Systems Biology

GitHub Events

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Last synced: over 2 years ago

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  • Total Commits: 170
  • Total Committers: 9
  • Avg Commits per committer: 18.889
  • Development Distribution Score (DDS): 0.4
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Top Committers
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Sven Thiele s****8@g****m 102
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Sven Thiele t****s@p****e 6
Clémence Frioux c****x 6
cfrioux c****x@g****m 5
cfrioux c****x@i****r 2
Sven Thiele s****e@u****e 1
sherman d****n@i****r 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 17
  • Total pull requests: 27
  • Average time to close issues: 2 months
  • Average time to close pull requests: 3 days
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  • Average comments per issue: 3.71
  • Average comments per pull request: 0.41
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Past Year
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  • Average time to close issues: N/A
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  • Average comments per issue: 0
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enhancement (2) documentation (2) bug (1) question (1)
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Packages

  • Total packages: 2
  • Total downloads:
    • pypi 43 last-month
  • Total dependent packages: 1
    (may contain duplicates)
  • Total dependent repositories: 11
    (may contain duplicates)
  • Total versions: 19
  • Total maintainers: 1
pypi.org: meneco

Metabolic Network Completion. Compute minimal completions to your draft network with reactions from a repair network.

  • Versions: 17
  • Dependent Packages: 1
  • Dependent Repositories: 9
  • Downloads: 36 Last month
Rankings
Dependent packages count: 4.7%
Dependent repos count: 4.9%
Forks count: 11.4%
Average: 11.4%
Stargazers count: 17.7%
Downloads: 18.5%
Maintainers (1)
Last synced: 11 months ago
pypi.org: meneco-gui

A graphical user interface for meneco.

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 2
  • Downloads: 7 Last month
Rankings
Dependent packages count: 10.0%
Forks count: 11.4%
Dependent repos count: 11.6%
Stargazers count: 17.7%
Average: 20.4%
Downloads: 51.5%
Maintainers (1)
Last synced: 11 months ago

Dependencies

.github/workflows/main.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v1 composite
.github/workflows/publish-to-test-pypi.yml actions
  • actions/checkout master composite
  • actions/setup-python v1 composite
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setup.py pypi
  • clyngor_with_clingo *