Python LCS Implementations (GALE & GAssist) for SNP Environment

Urbanowicz_GAssist_2010

Urbanowicz_GALE_2010

The above .zip files contain open source python implementations of existing LCS algorithms (GALE & GAssist) written/modified to accommodate SNP (single nucleotide polymorphism) gene association studies. These are the implementations used in the following paper recently accepted at PPSN:

R.J. Urbanowicz, J.H Moore. The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis
in Association Studies. PPSN 2010

This entry was posted in Software. Bookmark the permalink.

3 Responses to Python LCS Implementations (GALE & GAssist) for SNP Environment

  1. Pingback: Xavier Llorà » Blog Archive » GAssist and GALE Now Available in Python

  2. Arech says:

    Hi!
    There’s a wrong link for GALE file. It points to GAssist.zip, while should point to http://gbml.org/wp-content/uploads/2010/06/Urbanowicz_GALE_2010.zip

    Anyway, big thanks for sharing! I’ll try to use it in my studies…

Leave a Reply

Your email address will not be published. Required fields are marked *