• Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci Book Section, Stephen D. Turner, Scott M. Dudek, Marylyn D. Ritchie, Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini, http://link.springer.com/chapter/10.1007/978-3-642-12211-8_8, ©2010 Springer-Verlag Berlin Heidelberg, Lecture Notes in Computer Science, Springer Berlin Heidelberg, 86-97, 978-3-642-12210-1, 978-3-642-12211-8, 2010/01/01, 2014-02-24 18:05:57, 6023, link.springer.com, Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this “missing” heritability. Here we present our assessment of the performance of grammatical evolution to evolve neural networks (GENN) for discovering gene-gene interactions which contribute to a quantitative heritable trait. We present several modifications to the GENN procedure which result in modest improvements in performance., Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics,