Classifying G-protein-coupled receptors to the finest subtype level

Overington, 2006, How many drug targets are there?, Nat. Rev. Drug Discov., 5, 993, 10.1038/nrd2199 Rosenbaum, 2009, The structure and function of G-protein-coupled receptors, Nature, 459, 356, 10.1038/nature08144 Vaidehi, 2002, Prediction of structure and function of G protein-coupled receptors, Proc. Natl. Acad. Sci. USA, 99, 12622, 10.1073/pnas.122357199 Vroling, 2011, GPCRDB: information system for G protein-coupled receptors, Nucleic Acids Res., 39, D309, 10.1093/nar/gkq1009 Davies, 2007, On the hierarchical classification of G protein-coupled receptors, Bioinformatics, 23, 3113, 10.1093/bioinformatics/btm506 Gao, 2006, Classification of G-protein coupled receptors at four levels, Protein Eng. Des. Sel., 19, 511, 10.1093/protein/gzl038 Peng, 2010, An improved classification of G-protein-coupled receptors using sequence-derived features, BMC Bioinformatics, 11, 420, 10.1186/1471-2105-11-420 Lopez, 2003, WU-Blast2 server at the European Bioinformatics Institute, Nucleic Acids Res., 31, 3795, 10.1093/nar/gkg573 Davies, 2007, Proteomic applications of automated GPCR classification, Proteomics, 7, 2800, 10.1002/pmic.200700093 Chou, 2005, Prediction of G-protein-coupled receptor classes, J. Proteome Res., 4, 1413, 10.1021/pr050087t Elrod, 2002, A study on the correlation of G-protein-coupled receptor types with amino acid composition, Protein Eng., 15, 713, 10.1093/protein/15.9.713 Bhasin, 2004, GPCRpred: an SVM-based method for prediction of families and subfamilies of G-protein coupled receptors, Nucleic Acids Res., 32, W383, 10.1093/nar/gkh416 Huang, 2004, Classifying G-protein coupled receptors with bagging classification tree, Comput. Biol. Chem., 28, 275, 10.1016/j.compbiolchem.2004.08.001 Bhasin, 2005, GPCRsclass: a web tool for the classification of amine type of G-protein-coupled receptors, Nucleic Acids Res., 33, W143, 10.1093/nar/gki351 Gao, 2008, Classification of amine type G-protein coupled receptors with feature selection, Protein Pept. Lett., 15, 834, 10.2174/092986608785203755 Lin, 2009, GPCR-GIA: a web-server for identifying G-protein coupled receptors and their families with grey incidence analysis, Protein Eng. Des. Sel., 22, 699, 10.1093/protein/gzp057 Ur-Rehman, 2011, G-protein-coupled receptor prediction using pseudo-amino-acid composition and multiscale energy representation of different physiochemical properties, Anal. Biochem., 412, 173, 10.1016/j.ab.2011.01.040 Qiu, 2009, Prediction of G-protein-coupled receptor classes based on the concept of Chou’s pseudo amino acid composition: an approach from discrete wavelet transform, Anal. Biochem., 390, 68, 10.1016/j.ab.2009.04.009 Gu, 2010, Prediction of G-protein-coupled receptor classes in low homology using Chou’s pseudo amino acid composition with approximate entropy and hydrophobicity patterns, Protein Pept. Lett., 17, 559, 10.2174/092986610791112693 Karchin, 2002, Classifying G-protein coupled receptors with support vector machines, Bioinformatics, 18, 147, 10.1093/bioinformatics/18.1.147 Guo, 2006, Classifying G protein-coupled receptors and nuclear receptors on the basis of protein power spectrum from fast Fourier transform, Amino Acids, 30, 397, 10.1007/s00726-006-0332-z Xiao, 2009, GPCR-CA: a cellular automaton image approach for predicting G-protein-coupled receptor functional classes, J. Comput. Chem., 30, 1414, 10.1002/jcc.21163 Gupta, 2008, A novel and efficient technique for identification and classification of GPCRs, IEEE Trans. Inf. Technol. Biomed., 12, 541, 10.1109/TITB.2007.911308 Chou, 2002, Bioinformatical analysis of G-protein-coupled receptors, J. Proteome Res., 1, 429, 10.1021/pr025527k Kristiansen, 2004, Molecular mechanisms of ligand binding, signaling, and regulation within the superfamily of G-protein-coupled receptors: molecular modeling and mutagenesis approaches to receptor structure and function, Pharmacol. Ther., 103, 21, 10.1016/j.pharmthera.2004.05.002 Li, 2006, Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences, Bioinformatics, 22, 1658, 10.1093/bioinformatics/btl158 SCOP ASTRAL website. <http://scop.berkeley.edu>/. Vapnik, 1998 C.C. Chang, C.J. Lin, LIBSVM: a library for support vector machines, ACM Trans. Int. Syst. Technol. 2 (27) (2011) 1–27. Software is available at <http://www.csie.ntu.edu.tw/≃cjlin/libsvm>. Chou, 2001, Prediction of protein cellular attributes using pseudo-amino acid composition, Proteins, 43, 246, 10.1002/prot.1035 Chou, 2011, Some remarks on protein attribute prediction and pseudo amino acid composition, J. Theor. Biol., 273, 236, 10.1016/j.jtbi.2010.12.024 Shen, 2008, PseAAC: a flexible web server for generating various kinds of protein pseudo amino acid composition, Anal. Biochem., 373, 386, 10.1016/j.ab.2007.10.012 Gao, 2009, Prediction of nuclear receptors with optimal pseudo amino acid composition, Anal. Biochem., 387, 54, 10.1016/j.ab.2009.01.018 Gao, 2012, Prediction of pattern recognition receptor family using pseudo-amino acid composition, Biochem. Biophys. Res. Commun., 417, 73, 10.1016/j.bbrc.2011.11.057 Chou, 2005, Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes, Bioinformatics, 21, 10, 10.1093/bioinformatics/bth466