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

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. Categories and Subject Descriptors J.3. [Computer applications]: Life and Medical Sciences – biology and genetics. I.2.6 Learning General Terms: Algorithms, Experimentation Keywords Genetic Algorithm, Protein Localisation, Classifier Learning.

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Greg Paperin
• Keywords: GECCO 2008, Genetic Algorithm, Machine Learning Techniques, Multi-class Location Classifier, Optimization