GPCRTree: online hierarchical classification of GPCR function

Davies, Matthew N. and Secker, Andrew D. and Halling-Brown, Mark and Moss, David S. and Freitas, Alex A. and Timmis, Jon and Clark, Edward and Flower, Darren R. (2008) GPCRTree: online hierarchical classification of GPCR function. BMC Research Notes, 1 (67). 5 pages. ISSN 1756-0500. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1186/1756-0500-1-67

Abstract

G protein-coupled receptors (GPCRs) play important physiological roles transducing extracellular signals into intracellular responses. Approximately 50% of all marketed drugs target a GPCR. There remains considerable interest in effectively predicting the function of a GPCR from its primary sequence. FINDINGS: Using techniques drawn from data mining and proteochemometrics, an alignment-free approach to GPCR classification has been devised. It uses a simple representation of a protein's physical properties. GPCRTree, a publicly-available internet server, implements an algorithm that classifies GPCRs at the class, sub-family and sub-subfamily level. CONCLUSION: A selective top-down classifier was developed which assigns sequences within a GPCR hierarchy. Compared to other publicly available GPCR prediction servers, GPCRTree is considerably more accurate at every level of classification.

Item Type: Article
Uncontrolled keywords: classification, data mining, bioinformatics
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 29 Mar 2010 12:12
Last Modified: 19 May 2014 15:57
Resource URI: https://kar.kent.ac.uk/id/eprint/24050 (The current URI for this page, for reference purposes)
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