Kumar, Manish and Raghava, G.P.S. (2009) Prediction of nuclear proteins using SVM and HMM models. BMC bioinformatics, 10. p. 22. ISSN 1471-2105
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Abstract
This study describes a highly accurate method for predicting nuclear proteins. SVM module has been developed for the first time using SAAC for predicting nuclear proteins, where amino acid composition of N-terminus and the remaining protein were computed separately. In addition, our study is a first documentation where exclusively nuclear and non-nuclear domains have been identified and used for predicting nuclear proteins. The performance of the method improved further by combining both approaches together.
Item Type: | Article |
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Additional Information: | Open Access |
Subjects: | Q Science > QH Natural history > QH301 Biology QH301 Biology |
Depositing User: | Dr. K.P.S.Sengar |
Date Deposited: | 08 Dec 2011 19:36 |
Last Modified: | 08 Dec 2011 19:36 |
URI: | http://crdd.osdd.net/open/id/eprint/570 |
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