creators_name: Garg, Aarti
creators_name: Bhasin, Manoj
creators_name: Raghava, G.P.S.
type: article
datestamp: 2012-01-08 05:43:58
lastmod: 2012-01-08 05:43:58
metadata_visibility: show
title: Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search.
ispublished: pub
subjects: QD
full_text_status: restricted
note: Copyright of this article belongs to ASBMB.
abstract: Here we report a systematic approach for predicting subcellular localization (cytoplasm, mitochondrial, nuclear, and plasma membrane) of human proteins. First, support vector machine (SVM)-based modules for predicting subcellular localization using traditional amino acid and dipeptide (i + 1) composition achieved overall accuracy of 76.6 and 77.8%, respectively. PSI-BLAST, when carried out using a similarity-based search against a nonredundant data base of experimentally annotated proteins, yielded 73.3% accuracy. To gain further insight, a hybrid module (hybrid1) was developed based on amino acid composition, dipeptide composition, and similarity information and attained better accuracy of 84.9%. In addition, SVM modules based on a different higher order dipeptide i.e. i + 2, i + 3, and i + 4 were also constructed for the prediction of subcellular localization of human proteins, and overall accuracy of 79.7, 77.5, and 77.1% was accomplished, respectively. Furthermore, another SVM module hybrid2 was developed using traditional dipeptide (i + 1) and higher order dipeptide (i + 2, i + 3, and i + 4) compositions, which gave an overall accuracy of 81.3%. We also developed SVM module hybrid3 based on amino acid composition, traditional and higher order dipeptide compositions, and PSI-BLAST output and achieved an overall accuracy of 84.4%. A Web server HSLPred (www.imtech.res.in/raghava/hslpred/ or bioinformatics.uams.edu/raghava/hslpred/) has been designed to predict subcellular localization of human proteins using the above approaches.
date: 2005-04-15
date_type: published
publication: The Journal of biological chemistry
volume: 280
number: 15
publisher: ASBMB
pagerange: 14427-32
refereed: TRUE
issn: 0021-9258
official_url: http://www.jbc.org/content/280/15/14427.long
related_url_url: http:www.imtech.res.in/raghava/hslpred
related_url_type: author
citation:   Garg, Aarti and Bhasin, Manoj and Raghava, G.P.S.  (2005) Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search.  The Journal of biological chemistry, 280 (15).  pp. 14427-32.  ISSN 0021-9258     
document_url: http://crdd.osdd.net/open/193/1/raghava2005.pdf