title: Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles.
creator: Verma, Ruchi
creator: Tiwari, Ajit
creator: Kaur, Sukhwinder
creator: Varshney, Grish C
creator: Raghava, G.P.S.
subject: QH301 Biology
description: This study demonstrates that secretory proteins have different residue composition than non-secretory proteins. Thus, it is possible to predict secretory proteins from its residue composition-using machine learning technique. The multiple sequence alignment provides more information than sequence itself. Thus performance of method based on PSSM profile is more accurate than method based on sequence composition. A web server PSEApred has been developed for predicting secretory proteins of malaria parasites,the URL can be found in the Availability and requirements section.
publisher: BIomedcentral
date: 2008
type: Article
type: PeerReviewed
format: application/pdf
identifier: http://crdd.osdd.net/open/604/1/raghava08.1.pdf
relation: http://www.biomedcentral.com/1471-2105/9/201/
identifier:   Verma, Ruchi and Tiwari, Ajit and Kaur, Sukhwinder and Varshney, Grish C and Raghava, G.P.S.  (2008) Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles.  BMC bioinformatics, 9.  pp. 1-11.  ISSN 1471-2105     
relation: http://crdd.osdd.net/open/604/