Supervised ensembles of prediction methods for subcellular localization.
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 their theoretical properties, we propose to combine a well-balanced set of existing approaches to new, ensemble-based prediction methods. The experimental evaluation shows that our ensembles improve substantially over the underlying base methods.
Assfalg
Johannes
J
Institute for Informatics, Ludwig-Maximilians-Universität München, Oettingenstrasse 67, 80538 Munich, Germany. assfalg@dbs.ifi.lmu.de
Gong
Jing
J
Kriegel
Hans-Peter
HP
Pryakhin
Alexey
A
Wei
Tiandi
T
Zimek
Arthur
A