Neet: Simulating and analyzing network models

Neet is a python package designed to provide an easy-to-use API for creating and evaluating network models. In its current state, Neet supports simulating synchronous Boolean network models, though the API is designed to be model generic. Future work will implement asynchronous update mechanisms and more general network types.

If you are interested in using Neet, you'll definitely be interested in checking out the documentation - https://elife-asu.github.io/Neet.

Build Status

Installation

Via Pip

To install via pip, you can run the following

$ pip install neet

Note that on some systems this will require administrative privileges. If you don't have admin privileges or would prefer to install Neet for your user only, you do so via the --user flag:

$ pip install --user neet

From Source

$ git clone https://github.com/elife-asu/neet
$ cd neet
$ python setup.py test
$ pip install .

Getting Help

Neet is developed to help people interested in using and analyzing network models to get things done quickly and painlessly. Your feedback is indispensable. Please create an issue if you find a bug, an error in the documentation, or have a feature you'd like to request. Your contribution will make Neet a better tool for everyone.

If you are interested in contributing to Neet, please contact the developers. We'll get you up and running!

Neet Source Repository

https://github.com/elife-asu/neet

Neet Issue Tracker

https://github.com/elife-asu/neet/issues

Relevant Publications

• Daniels, B.C., Kim, H., Moore, D.G., Zhou, S., Smith, H.B., Karas, B., Kauffman, S.A., and Walker, S.I. (2018) "Criticality Distinguishes the Ensemble of Biological Regulatory Networks" Phys. Rev. Lett. 121 (13), 138102, doi:10.1103/PhysRevLett.121.138102

System Support

So far the python wrapper has been tested under python2.7, python3.4 and python3.5, and on the following platforms:

• Debian 8
• Mac OS X 10.11 (El Capitan)
• Windows 10

Copyright and Licensing

Copyright © 2017-2019 Bryan C. Daniels, Bradley Karas, Hyunju Kim, Douglas G. Moore, Harrison Smith, Sara I. Walker, and Siyu Zhou. Free use of this software is granted under the terms of the MIT License.

See the LICENSE for details.