Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins
Publication Type:Conference Poster
Source:Genetic and Evolutionary Computation Conference 2008 (GECCO’08), Atlanta, USA. Association for Computing Machinery, pp. 1135-1136.
Keywords:protein localisation; classifier; machine learning; pattern learning
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.