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Integrated Statistical And Machine Learning Algorithms For Predicting And Classifying G Protein-Coupled Receptors, Fredrick Ayivor

Open Access Theses & Dissertations

G protein-coupled receptors (GPCRs) are transmembrane proteins with important functions in signal transduction and often serve as drug targets. With increasing availability of protein sequence information, there is much interest in computationally predicting GPCRs and classifying them according to their biological roles. Such predictions are cost-efficient and can be valuable guides for designing wet lab experiments to help elucidate signaling pathways and expedite drug discovery. There are existing computational tools of GPCR prediction that involve principal component analysis (PCA), intimate sorting (IS), support vector machine, and random forest (RF) techniques using various sequence derived features. While accuracies of over 90\% …