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BetaTPred: prediction of beta-TURNS in a protein using statistical algorithms.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title BetaTPred: prediction of beta-TURNS in a protein using statistical algorithms.
 
Creator Kaur, Harpreet
Raghava, G.P.S.
 
Subject QR Microbiology
 
Description MOTIVATION: beta-turns play an important role from a structural and functional point of view. beta-turns are the most common type of non-repetitive structures in proteins and comprise on average, 25% of the residues. In the past numerous methods have been developed to predict beta-turns in a protein. Most of these prediction methods are based on statistical approaches. In order to utilize the full potential of these methods, there is a need to develop a web server.

RESULTS: This paper describes a web server called BetaTPred, developed for predicting beta-TURNS in a protein from its amino acid sequence. BetaTPred allows the user to predict turns in a protein using existing statistical algorithms. It also allows to predict different types of beta-TURNS e.g. type I, I', II, II', VI, VIII and non-specific. This server assists the users in predicting the consensus beta-TURNS in a protein
 
Publisher Oxford University Press
 
Date 2002-03
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/273/1/raghava2002.pdf
Kaur, Harpreet and Raghava, G.P.S. (2002) BetaTPred: prediction of beta-TURNS in a protein using statistical algorithms. Bioinformatics (Oxford, England), 18 (3). pp. 498-9. ISSN 1367-4803
 
Relation http://bioinformatics.oxfordjournals.org/content/18/3/498.long
http://crdd.osdd.net/open/273/