Davies, M.N. and Secker, A. and Halling-Brown, M. and Moss, D.S. and Freitas, A.A. and Timmis, J. and Clark, E. and Flower, D.R. (2008) GPCRTree: online hierarchical classification of GPCR function. BMC Research Notes, 1 (67). 5 pages. ISSN 1756-0500.
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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: | 29 Mar 2010 12:12 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/24050 (The current URI for this page, for reference purposes) |
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