ICAR Research Data Repository for Knowledge Management
Prediction of nuclear proteins using SVM and HMM models.
DIR@IMTECH: CSIR-Institute of Microbial Technology
View Archive Info| Field | Value | |
| Title |
Prediction of nuclear proteins using SVM and HMM models.
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| Creator |
Kumar, Manish
Raghava, G.P.S. |
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| Subject |
QH301 Biology
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| Description |
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.
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| Publisher |
BIomedcentral
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| Date |
2009
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| Type |
Article
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://crdd.osdd.net/open/570/2/raghava09.1.pdf
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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| Relation |
http://www.biomedcentral.com/content/pdf/1471-2105-10-22.pdf
http://crdd.osdd.net/open/570/ |
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