minepy - Maximal Information-based Nonparametric Exploration¶
minepy provides an ANSI C 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);
- a C++ interface;
- an efficient Python API;
- an efficient MATLAB/OCTAVE API;
- a command-line application similar to the original
- the minerva R interface is available at CRAN.
minepy is an open-source, GPLv3-licensed software.
NEWS: MICtools, a comprehensive and effective pipeline for TICe and MICe analysis is now available. 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: https://www.biorxiv.org/content/early/2017/11/07/215855, code and documentation: https://github.com/minepy/mictools. The minepy library is preinstalled in the Docker image: https://hub.docker.com/r/minepy/mictools/.
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