FuNeL - Functional Network Learning protocol

FuNeL is a protocol to infer functional networks from machine learning models. It is a general approach that uses BioHEL, a rule-based evolutionary classifier, to describe the expression samples as a set of rules and then infers interactions between genes that act together within rules to predict the samples class. FuNeL generates co-prediction networks, that capture biological knowledge complementary to that contained in popular similarity-based co-expression networks.

Documentation

In order to learn how to use FuNeL read the tutorial. It explains the installation requirements and protocol settings and demonstrates how to run the scripts.

Download

Feel free to download the beta version of FuNeL scripts (GNU GPLv3) and if you have any comments, we would be very happy to hear them.

Project team

• Nicola Lazzarini
• Paweł Widera
• Jaume Bacardit
• Natalio Krasnogor

Publications

• DOI eprint code BibTeX
  N. Lazzarini, P. Widera, S. Williamson, R. Heer, N. Krasnogor, J. Bacardit
  Functional networks inference from rule-based machine learning models
  in BioData Mining, 9(1), December 2016

  @ARTICLE{Lazzarini2016,
    title = {Functional networks inference from rule-based machine learning models},
    author = {Lazzarini, Nicola and Widera, Paweł and Williamson, Stuart and Heer, Rakesh and Krasnogor, Natalio and Bacardit, Jaume},
    year = 2016,
    doi = {10.1186/s13040-016-0106-4},
    month = dec,
    journal = {BioData Mining},
    volume = {9},
    number = {1}