creators_name: Kumar, Manish
creators_name: Raghava, G.P.S.
type: article
datestamp: 2011-12-08 19:36:10
lastmod: 2011-12-08 19:36:10
metadata_visibility: show
title: Prediction of nuclear proteins using SVM and HMM models.
ispublished: pub
subjects: QH301
full_text_status: public
note: Open Access
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.
date: 2009
date_type: published
publication: BMC bioinformatics
volume: 10
publisher: BIomedcentral
pagerange: 22
refereed: TRUE
issn: 1471-2105
official_url: http://www.biomedcentral.com/content/pdf/1471-2105-10-22.pdf
related_url_url: http://www.biomedcentral.com/content/pdf/1471-2105-10-22.pdf
related_url_type: pub
citation:   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     
document_url: http://crdd.osdd.net/open/570/2/raghava09.1.pdf