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