Prediction of protein subcellular locations using support vector machines

Authors:
Na-na Li;Xiao-hui Niu;Feng Shi;Xue-yan Li
Affiliations:
School of Science, Huazhong Agriculture University;School of Science, Huazhong Agriculture University;School of Science, Huazhong Agriculture University;College of Sciences, Civil Aviation University of China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

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Support-Vector Networks

Machine Learning

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Abstract

In this paper,we constructed a data set of rice proteins with known locations from SWISS-PROT,using the Support Vector Machine to predicte the type of a given rice protein by incorporating sequence information with physics chemistry property of amino acid. Results are assessed through 5-fold cross-validation tests.