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Maximal Information-based Nonparametric Exploration
in C, C++, Python and MATLAB/Octave

minepy provides an ANSI C library (with C++, Python and MATLAB/OCTAVE wrappers) for Maximal Information-based Nonparametric Exploration (MIC and MINE family)

minepy contains:

minepy is multiplatform (Linux, Mac OS X and Windows Xp, Vista and 7), it works with Python 2 and 3 and it is Open Source, distributed under the GNU General Public License version 3.

If you use minepy, please cite:

Bioinformatics Cover 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.

[Abstract] [Full Text (HTML)] [Full Text (PDF)] [Supplementary Data] [Download citation]

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The latest release of minepy is 1.0.0 (released 2013-03-05). You can download it as a source, as Windows installers and as Windows stand-alone executable. (Download).

You can contribute via Pull Requests through the official github repository.


Old Documentation:

If you still have questions, feel free to send an email to davide.albanese AT


Developer: Davide Albanese (davide.albanese AT

Contributors: Michele Filosi (filosi AT

MINE Original Paper

D. Reshef, Y. Reshef, H. Finucane, S. Grossman, G. McVean, P. Turnbaugh, E. Lander, M. Mitzenmacher, P. Sabeti. Detecting novel associations in large datasets. Science 334, 6062 (2011) (

Financial Contributions

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Predictive Models for Biological Predictive Models for Biological and Environmental Data Analysis (MPBA) Research Unit at Fondazione Bruno Kessler

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Research and Innnovation Center - Fondazione Edmund Mach

Last update: 05 March 2013
by Davide Albanese.

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