Science Score: 33.0%

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

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: nature.com
  • Committers with academic emails
    17 of 25 committers (68.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: rxncon
  • License: lgpl-3.0
  • Language: Python
  • Default Branch: master
  • Size: 5.15 MB
Statistics
  • Stars: 10
  • Watchers: 1
  • Forks: 2
  • Open Issues: 1
  • Releases: 0
Created over 9 years ago · Last pushed almost 4 years ago
Metadata Files
Readme License

README.md

rxncon

The purpose of rxncon is to provide a framework to collect, visualise and model experimental data on cellular networks. In the rxncon framework, cellular signal transduction networks are described at the same granularity as empirical data. The key feature is strict separation of elemental reactions from contingencies, which define contextual constrains on these reactions, and this separation minimises the combinatorial complexity. The user defines the network as one reaction list and one contingency list. From these data mathematical and graphical representation can be generated. The network can be easily modified and extended, and both visualization and mathematical models can be generated automatically at any time.

For more details we refer to the following publications:

  • Tiger, C.-F., Krause, F., Cedersund, G., Palmér, R., Klipp. E., Hohmann, S., Kitano, H. & Krantz, M. (2012) A framework for mapping, visualisation and automatic model creation of signal transduction networks. Molecular Systems Biology 8, 578.

  • Romers, J.C. & Krantz, M. (2017) rxncon 2.0: a language for executable molecular systems biology. bioRxiv:107136

Installation

This software requires Python 3.5 or higher. Installation is straightforward through the Python Package Index. If the pip command is linked to your Python 3 installation, run pip install rxncon, otherwise run pip3 install rxncon.

This should install all libraries and the command-line tools to interface with them on your machine.

Usage

Please clone our models repository to find an example model describing the insulin pathway, as well as an example Excel sheet that you can use to create your own models.

In what follows we assume the Excel file containing your network description is called model.xls

Compiling to a boolean network

To compile the rxncon system to a boolean network, run the command rxncon2boolnet.py model.xls This will generate three files model.boolnet, model_symbols.csv and model_initial_vals.csv

Compiling to a rule-based model

Generating graphs

For devs

We accept pull requests. Some things to keep in mind:

  • Please write tests for your code. The directory structure in rxncon/test/ mirrors the structure in the rxncon/ directory, and we try to cover each module. Feel free to look around. The testing framework we use is pytest

  • Please provide some documentation for each module, class, method and function. Don't overdo it either: one-liner functions don't require 5 lines of documentation.

  • Please use Python 3.5's type annotations in your code. The shell script typecheck.sh runs the mypy type checker with the strictest options. This should give no errors.

Owner

  • Login: rxncon
  • Kind: user

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 1,104
  • Total Committers: 25
  • Avg Commits per committer: 44.16
  • Development Distribution Score (DDS): 0.697
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Jesper Romers j****s@g****m 334
thieme s****e@h****e 226
Jesper Romers j****s@h****e 157
Sebastian s****e@b****e 114
jesperromers j****s@j****l 114
Basti d****l@l****t 72
Jesper Romers j****r@j****l 16
Mathias Wajnberg m****g@f****e 12
Mathias Wajnberg m****g@h****e 7
jesperromers j****s@c****e 7
Marcus m****5@g****m 6
jesperromers j****s@c****e 6
Mathias Wajnberg M****g@h****e 5
jesperromers j****s@c****e 4
jesperromers j****s@c****e 4
jesperromers j****s@c****e 3
jesperromers j****s@c****e 3
jesperromers j****s@j****n 3
jesperromers j****s@c****e 2
jesperromers j****s@c****e 2
jesperromers j****s@j****3 2
palmerito0 s****s@g****m 2
jesperromers j****s@c****e 1
jesperromers j****s@c****e 1
jesperromers j****s@c****e 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 1
  • Total pull requests: 3
  • Average time to close issues: almost 2 years
  • Average time to close pull requests: 12 months
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.67
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • palmerito0 (1)
Pull Request Authors
  • palmerito0 (2)
  • lenarother (1)
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 51 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 17
  • Total maintainers: 2
pypi.org: rxncon

The reaction-contingency framework for cellular signalling processes.

  • Versions: 17
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 51 Last month
Rankings
Dependent packages count: 10.0%
Stargazers count: 17.7%
Average: 18.9%
Forks count: 19.1%
Dependent repos count: 21.7%
Downloads: 26.0%
Maintainers (2)
Last synced: 11 months ago

Dependencies

setup.py pypi
  • click *
  • click_log ==0.1.8
  • colorama *
  • networkx *
  • numpy *
  • pyeda *
  • pytest *
  • scipy *
  • xlrd *