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The Analysis Tool for Heritable and Environmental Network Associations (ATHENA) is a software package that combines statistical and biological variable selection methods with machine learning modeling techniques to identify complex prediction models that can include non-linear interactions and different types of high-throughput data.

ATHENA was developed to integrate biological data to perform feature/variable selection and modeling of complex genetic effects. In addition, ATHENA, a multi-functional software package, was designed to perform the three main functions essential to determine the meta-dimensional models of complex disease:(1) performing feature/variable selections from categorical or continuous independent variables;(2) modeling main and interaction effects that explain or predict categorical or continuous clinical outcomes;(3) interpreting the significant models for use in further translational bioinformatics.ATHENA contains filtering components, modeling components, and an evolutionary computing approach based on a machine technique to generate complex models. This version of ATHENA contains the computational evolution modeling method Grammatical Evolution Neural Networks (GENN).

The original version of ATHENA was written in C++. This new version of the project is written in Python to make installation and use of the package easier. It also allows for easier experimentation with different evolutionary algorithm techniques to improve the functioning of the software.

The original code can be found on the Ritchie Lab website.