Python implementation and expansion of ATHENA to include recent advances in evolutionary computing.
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).
ATHENA documentation is available at https://ritchielab.github.io/athena-python/