Affiliation:
1. Institute for Informatics, Ludwig-Maximilians-Universität München, Oettingenstrasse 67, 80538 Munich, Germany
Abstract
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.
Publisher
World Scientific Pub Co Pte Lt
Subject
Computer Science Applications,Molecular Biology,Biochemistry
Cited by
8 articles.
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