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Title:
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PREDICTION OF PROTEIN FUNCTION USING LEARNING CLASSIFIER SYSTEMS |
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Author(s):
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Luiz Melo Romão, Júlio César Nievola |
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ISBN:
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978-989-8533-06-7 |
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Editors:
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Hans Weghorn, Leonardo Azevedo and Pedro Isaías |
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Year:
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2011 |
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Edition:
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Single |
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Keywords:
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Hierarchical Classification, Protein Function Prediction, Classifiers Systems |
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Type:
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Full Paper |
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First Page:
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395 |
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Last Page:
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401 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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There are several problems that have been studied by Bioinformatics and one, which stands out, is the prediction of the proteins functions. This paper shows a novel solution for hierarchical classification problems based on Learning Classifier Systems. The proposed algorithm HLCS-Flat was designed to work with protein functions prediction within structured ontologies represented as a directed acyclic graph and provides positives results when compared to the well-known rule-based classification method RIPPER. This paper presents the concepts of hierarchical classification and classifier systems, and also the HLCS-Flat model and its computational results. |
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