semvec/pypi-packages huggingface dataset:
metadisassembler 0.1.0
The Metabolic Disassembler
License: MIT
Keywords: biosynthesis,metabolic pathway,natural product,cheminformatics

The Metabolic Disassembler
==========================

The Metabolic Disassembler is a Python package to automatically predict
a combination of biosynthetic units in a natural product. This software
would help to reveal the starting materials of the target natural
product.

Installation
------------

Install The Metabolic Disassembler with ``pip``.

.. code:: bash

   $ pip install metadisassembler

Requirements
------------

-  Python (3.6)

   -  `RDKit <https://www.rdkit.org>`__ (version 2019.09.2.0)
   -  `NetworkX <https://networkx.github.io/documentation/stable/>`__
      (version 2.2)
   -  `CairoSVG <https://cairosvg.org>`__ (version 2.4.2)
   -  `Pillow (PIL) <https://pillow.readthedocs.io/en/stable/>`__
      (version 6.2.1)
   -  `Pandas <https://pandas.pydata.org>`__ (version 0.25.3)
   -  `Matplotlib <https://matplotlib.org>`__ (version 3.1.2)

Command Line Usage
------------------

.. code:: bash

   % metadisassembler -h
   usage: metadisassembler [-h] [-t TIME] [--hide] [-c] query

   positional arguments:
     query                 MDL_Molfile, SMILES, InChI, KEGG_COMPOUND_ID,
                           KNApSAcK_COMPOUND_ID

   optional arguments:
     -h, --help            show this help message and exit
     -t TIME, --time TIME  set a time limit [s] [default: 300]
     --hide                hide stereochemistry [default: False]
     -c, --color           output color allocation information [default: False]

Basic Usage
-----------

A usage example by Jupyter Notebook can be seen
`here <https://github.com/the-metabolic-disassembler/metadisassembler/blob/master/jupyter_usecase/basic_usage.ipynb>`__.

Google Colab
------------

You can try the process from installation to the basic usage in Google
Colab. |colab-logo|

Citation
--------

Amano K, Matsumoto T, Tanaka K, Funatsu K, Kotera M. Metabolic
disassembler for understanding and predicting the biosynthetic units of
natural products. *BMC Bioinformatics* **20**, 728 (2019)
`doi:10.1186/s12859-019-3183-9 <https://doi.org/10.1186/s12859-019-3183-9>`__

.. |colab-logo| image:: https://colab.research.google.com/assets/colab-badge.svg
   :target: https://colab.research.google.com/github/the-metabolic-disassembler/metadisassembler/blob/master/jupyter_usecase/basic_usage_in_colab.ipynb
ggui 1.2.0
gPhoton Graphical User Interface
License: MIT
Requires Python: >=3.6.0


# gGui: gPhoton glue user interface.
gGui is a data-analysis software written to visualize astronomical data, specifically time-tagged lightcurves, coadds, and cubes. gGui serves as the primary data visualization tool for [gPhoton](https://archive.stsci.edu/prepds/gphoton/), the data reduction pipeline for GALEX. 

Please see our full documentation at: https://ggui.readthedocs.io/

gGui is written atop the [Glue Python Library for Dataset Visualization](https://github.com/glue-viz/glue). 

## Installation Instructions:
* Install Python 3.6+
* Upgrade pip
```console
python -m pip install --upgrade pip
```
* Install gGui via pip
```console
pip install ggui
```

## Sample Usage
```console
ggui --target_list /path/to/ggui.yml
```
will automatically load a specific target list into a new gGui session.
```console
ggui --yaml_select
```
will open a file-select dialog to select your target list(s). After which, gGui will load these targets.

## Major Revision History
* 2019-12-22: Version 1.2 posted to GitHub/PyPI
* 2019-11-02: Version 1.1 posted to GitHub/PyPI
* 2019-06-20: Version 1.0 posted to GitHub/PyPI
* 2019-06-11: Uploaded first test of b0.3.5 to PyPI
* 2017-06-26: v0.3.0 Tag Created