PRED-GPCR: GPCR recognition and family classification server
Open Access
- 1 July 2004
- journal article
- research article
- Published by Oxford University Press (OUP) in Nucleic Acids Research
- Vol. 32 (Web Server) , W380-W382
- https://doi.org/10.1093/nar/gkh431
Abstract
The vast cell-surface receptor family of G-protein coupled receptors (GPCRs) is the focus of both academic and pharmaceutical research due to their key role in cell physiology along with their amenability to drug intervention. As the data flow rate from the various genome and proteome projects continues to grow, so does the need for fast, automated and reliable screening for new members of the various GPCR families. PRED-GPCR is a free Internet service for GPCR recognition and classification at the family level. A submitted sequence or set of sequences, is queried against the PRED-GPCR library, housing 265 signature profile HMMs corresponding to 67 well-characterized GPCR families. Users query the server through a web interface and results are presented in HTML output format. The server returns all single-motif matches along with the combined results for the corresponding families. The service is available online since October 2003 at http://bioinformatics.biol.uoa.gr/PRED-GPCR.Keywords
This publication has 13 references indexed in Scilit:
- The Pfam protein families databaseNucleic Acids Research, 2004
- A Novel method for GPCR recognition and family classification from sequence alone using signatures derived from profile hidden Markov modelsSAR and QSAR in Environmental Research, 2003
- GPCRDB information system for G protein-coupled receptorsNucleic Acids Research, 2003
- Seven-transmembrane receptorsNature Reviews Molecular Cell Biology, 2002
- Deriving structural and functional insights from a ligand-based hierarchical classification of G protein-coupled receptorsProtein Engineering, Design and Selection, 2002
- The PROSITE database, its status in 2002Nucleic Acids Research, 2002
- CAST: an iterative algorithm for the complexity analysis of sequence tractsBioinformatics, 2000
- Increased coverage of protein families with the Blocks Database serversNucleic Acids Research, 2000
- Profile hidden Markov models.Bioinformatics, 1998
- Hidden Markov models for sequence analysis: extension and analysis of the basic methodBioinformatics, 1996