minepy provides a library for the Maximal Information-based Nonparametric Exploration (MIC and MINE family). Key features:

• APPROX-MIC (the original algorithm, DOI: 10.1126/science.1205438) and MIC_e (DOI: arXiv:1505.02213 and DOI: arXiv:1505.02214) estimators;
• Total Information Coefficient (TIC, DOI: arXiv:1505.02213) and the Generalized Mean Information Coefficient (GMIC, DOI: arXiv:1308.5712);
• an ANSI C library
• a C++ interface;
• an efficient Python API (Python 2 and 3 compatibility);
• an efficient MATLAB/OCTAVE API;

minepy is an open-source, GPLv3-licensed software.

The minerva R interface is available at CRAN.

The `mine` command-line application is deprecated since version 1.2.2. We suggest to use MICtools, a comprehensive and effective pipeline for TICe and MICe analysis. TICe is used to perform efficiently a high throughput screening of all the possible pairwise relationships assessing their significance, while MICe is used to rank the subset of significant associations on the bases of their strength. Paper, code and documentation.

The minepy library is preinstalled in the MICtools Docker image.

• Homepage and Documentation
• Download
• Github page
• Issues
• Old (version 1.0.0) documentation

Davide Albanese, Michele Filosi, Roberto Visintainer, Samantha Riccadonna, Giuseppe Jurman and Cesare Furlanello. minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers. Bioinformatics (2013) 29(3): 407-408 first published online December 14, 2012 doi:10.1093/bioinformatics/bts707.

• Computational Biology Unit - Research and Innnovation Center at Fondazione Edmund Mach
• Predictive Models for Biological and Environmental Data Analysis (MPBA) Research Unit at Fondazione Bruno Kessler