Metadata-Version: 2.1
Name: sterope
Version: 1.1
Summary: Sterope: Sensitivity analysis of kappa Rule-Based Models based on Dynamic Influence Networks
Home-page: https://github.com/glucksfall/sterope
Author: Rodrigo Santibáñez
Author-email: glucksfall@users.noreply.github.com
License: GPLv3+
Project-URL: Manual, https://sterope.readthedocs.io
Project-URL: Bug Reports, https://github.com/glucksfall/sterope/issues
Project-URL: Source, https://github.com/glucksfall/sterope
Keywords: systems biology,stochastic modeling,parameter analysis
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Environment :: Console
Classifier: Operating System :: Unix
Requires-Python: >=3.0
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: salib
Requires-Dist: dask
Requires-Dist: dask-jobqueue

# sterope

Sterope is a python3 package that implement a method based on the Dynamic
Influence Network (https://www.ncbi.nlm.nih.gov/pubmed/28866584) to analyze the
sensitivity of parameter values in the response of a Rule-Based Model written in
kappa (https://kappalanguage.org/)

The plan to add methods into Pleiades (https://github.com/glucksfall/pleiades)
includes a parameterization employing a Particle Swarm Optimization protocol and
other analysis methods that are typical of frameworks like Ordinary Differential
Equations. You could write us if you wish to add methods into pleione or aid in
the development of them.


