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Proceedings of the 6th Asia-Pacific Bioinformatics Conference
In the past decade, many automated prediction methods for the subcellular localization of proteins have been proposed, utilizing a wide range of principles and learning approaches. Based on an experimental evaluation of different methods and on their theoretical properties, we propose to combine a well balanced set of existing approaches to new, ensemble-based prediction methods. The experimental evaluation shows our ensembles to improve substantially over the underlying base methods.doi:10.1142/9781848161092_0006 fatcat:ylhcv5hsxnbkfkpe7sziyvlgiy