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Protein function classification via support vector machine approach. (English) Zbl 1021.92008
Summary: Support vector machine (SVM) is introduced as a method for the classification of proteins into functionally distinguished classes. Studies are conducted on a number of protein classes including RNA-binding proteins; protein homodimers, proteins responsible for drug absorption, proteins involved in drug distribution and excretion, and drug metabolizing enzymes. Testing accuracy for the classification of these protein classes is found to be in the range of \(84-96 \%\). This suggests the usefulness of SVM in the classification of protein functional classes and its potential application in protein function prediction.

MSC:
92C40 Biochemistry, molecular biology
68T05 Learning and adaptive systems in artificial intelligence
68T10 Pattern recognition, speech recognition
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