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Building multiclass classifiers for remote homology detection and fold recognition
Authors:Huzefa Rangwala  George Karypis
Institution:(1) Department of Computer Science & Engineering, University of Minnesota, Minneapolis, Minnesota, USA
Abstract:

Background  

Protein remote homology detection and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective methods for solving these problems. These methods are primarily used to solve binary classification problems and they have not been extensively used to solve the more general multiclass remote homology prediction and fold recognition problems.
Keywords:
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