title: Prediction of nuclear proteins using SVM and HMM models.
creator: Kumar, Manish
creator: Raghava, G.P.S.
subject: QH301 Biology
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.
publisher: BIomedcentral
date: 2009
type: Article
type: PeerReviewed
format: application/pdf
identifier: http://crdd.osdd.net/open/570/2/raghava09.1.pdf
relation: http://www.biomedcentral.com/content/pdf/1471-2105-10-22.pdf
identifier:   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     
relation: http://crdd.osdd.net/open/570/