A feature generation algorithm for sequences with application to splice-site prediction

In this paper we present a new approach to feature selection for sequence data. We identify general feature categories and give construction algorithms for each of them. We show how they can be integrated in a system that tightly couples feature construction and feature selection. This integrated process, which we refer to as feature generation, allows us to systematically search a large space of potential features. We demonstrate the effectiveness of our approach for an important component of the gene finding problem, splice-site prediction. We show that predictive models built using our feature generation algorithm achieve a significant improvement in accuracy over existing, state-of-the-art approaches.