Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins

Abstract

A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. While traditional machine learning techniques present a black-box approach to this problem, the current method explicitly represents the discovered localisation motifs. A combined multi-class location classifier is presented and compared to other techniques based on genetic programming. Without consideration of additional structural information the presented method outperforms the alternative techniques.