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sygma

A python library for prediction of drug metabolites

https://github.com/3d-e-chem/sygma

Science Score: 67.0%

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

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: wiley.com, zenodo.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.3%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

A python library for prediction of drug metabolites

Basic Info
  • Host: GitHub
  • Owner: 3D-e-Chem
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Homepage: http://sygma.readthedocs.io
  • Size: 64.5 KB
Statistics
  • Stars: 17
  • Watchers: 2
  • Forks: 4
  • Open Issues: 4
  • Releases: 1
Created over 9 years ago · Last pushed almost 8 years ago
Metadata Files
Readme License Citation

README.rst 

SyGMa
=====
SyGMa is a python library for the **Sy**\ stematic **G**\ eneration of potential **M**\ et\ **a**\ bolites.
It is a reimplementation of the metabolic rules outlined in
`Ridder, L., & Wagener, M. (2008)
SyGMa: combining expert knowledge and empirical scoring in the prediction of metabolites.
ChemMedChem, 3(5), 821-832
`_.

.. image:: https://travis-ci.org/3D-e-Chem/sygma.svg?branch=master
    :target: https://travis-ci.org/3D-e-Chem/sygma
.. image:: https://api.codacy.com/project/badge/Grade/7f18ab1d1a80437f8e28ac1676c70519
    :target: https://www.codacy.com/app/3D-e-Chem/sygma?utm_source=github.com&utm_medium=referral&utm_content=3D-e-Chem/sygma&utm_campaign=Badge_Grade
.. image:: https://api.codacy.com/project/badge/Coverage/7f18ab1d1a80437f8e28ac1676c70519
    :target: https://www.codacy.com/app/3D-e-Chem/sygma?utm_source=github.com&utm_medium=referral&utm_content=3D-e-Chem/sygma&utm_campaign=Badge_Coverage
.. image:: https://img.shields.io/badge/docker-ready-blue.svg
    :target: https://hub.docker.com/r/3dechem/sygma
.. image:: https://anaconda.org/3d-e-chem/sygma/badges/installer/conda.svg
    :target: https://conda.anaconda.org/3d-e-chem
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1043307.svg
   :target: https://doi.org/10.5281/zenodo.1043307

Requirements
------------
SyGMa requires RDKit with INCHI support

Installation
------------
* Install with Anaconda: ``conda install -c 3d-e-Chem -c rdkit sygma``

OR

* Install RDKit following the instructions in http://www.rdkit.org/docs/Install.html

AND

* ``pip install sygma`` OR, after downloading sygma, ``python setup.py install``

Example: generating metabolites of phenol
-----------------------------------------
.. code-block:: python

    import sygma
    from rdkit import Chem

    # Each step in a scenario lists the ruleset and the number of reaction cycles to be applied
    scenario = sygma.Scenario([
        [sygma.ruleset['phase1'], 1],
        [sygma.ruleset['phase2'], 1]])

    # An rdkit molecule, optionally with 2D coordinates, is required as parent molecule
    parent = Chem.MolFromSmiles("c1ccccc1O")

    metabolic_tree = scenario.run(parent)
    metabolic_tree.calc_scores()

    print metabolic_tree.to_smiles()


Docker
------
SyGMa can be executed in a Docker (https://www.docker.com/) container as follows:

.. code-block:: bash

    docker run 3dechem/sygma c1ccccc1O

Owner

  • Name: 3D-e-Chem NLeSC project
  • Login: 3D-e-Chem
  • Kind: organization
  • Location: Amsterdam, The Netherlands

Software repositories for 3D-e-Chem project of Netherlands eScience Center

Citation (CITATION.cff) 

# YAML 1.2
# Metadata for citation of this software according to the CFF format (https://citation-file-format.github.io/)
cff-version: 1.0.3
message: If you use this software, please cite it as below.
title: SyGMa
doi: 10.5281/zenodo.1043307
authors:
- given-names: Lars
  family-names: Ridder
  affiliation: Netherlands eScience Center
version: 1.1.1
date-released: 2017-11-07
repository-code: https://github.com/3D-e-Chem/sygma
license: GPL-3.0
references:
- type: article
  doi: 10.1002/cmdc.200700312
  title: 'SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction
    of Metabolites'
  authors:
  - given-names: Lars
    family-names: Ridder
  - given-names: Markus
    family-names: Wagener

GitHub Events

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

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 59
  • Total Committers: 1
  • Avg Commits per committer: 59.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
ridderl l****r@e****l 59
Committer Domains (Top 20 + Academic)
esciencecenter.nl: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 8
  • Total pull requests: 0
  • Average time to close issues: 17 days
  • Average time to close pull requests: N/A
  • Total issue authors: 3
  • Total pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • 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
View more stats
Top Authors
Issue Authors
  • sverhoeven (6)
  • ridderl (1)
  • dmachalz (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Dependencies

environment.yml conda
  • future
  • rdkit
  • sphinx-argparse
  • sygma
requirements.txt pypi
  • nose *
  • sphinx *
  • sphinx-argparse *
  • sphinx_rtd_theme *
setup.py pypi
  • future *