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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Li, Nn., Niu, Xh., Shi, F., Li, Xy. (2005). Prediction of Protein Subcellular Locations Using Support Vector Machines. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_140
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DOI: https://doi.org/10.1007/11539087_140
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28323-2
Online ISBN: 978-3-540-31853-8
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