Classification of amine type G-protein coupled receptors with feature selection.
G-protein coupled receptors (GPCRs) are involved in various physiological processes. Therefore, classification of amine type GPCRs is important for proper understanding of their functions. Though some effective methods have been developed, it still remains unknown how many and which features are essential for this task. Empirical studies show that feature selection might address this problem and provide us with some biologically useful knowledge. In this paper, a feature selection technique is introduced to identify those relevant features of proteins which are potentially important for the prediction of amine type GPCRs. The selected features are finally accepted to characterize proteins in a more compact form. High prediction accuracy is observed on two data sets with different sequence similarity by 5-fold cross-validation test. The comparison with a previous method demonstrates the efficiency and effectiveness of the proposed method.
Gao
Qing-Bin
QB
Department of Health Statistics, Second Military Medical University, Shanghai 200433, China.
Wu
Cheng
C
Ma
Xiu-Qiang
XQ
Lu
Jian
J
He
Jia
J
D000588:Amines / Q000378:metabolism*; D001185:Artificial Intelligence; D030562:Databases, Protein; D004151:Dipeptides / Q000737:chemistry; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry / Q000145:classification* / Q000378:metabolism*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D000588:Amines; D004151:Dipeptides; D043562:Receptors, G-Protein-Coupled