Prediction of G Protein-Coupled Receptors with SVM-Prot Features and Random Forest

Lignende værker

• GPCRpred: an SVM-based method for prediction of families and subfamilies of G-protein coupled receptors
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• Using random forests for assistance in the curation of G-protein coupled receptor databases
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• Agonists of G‑Protein-Coupled Odorant Receptors Are Predicted from Chemical Features
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• In Silico Prediction of Gamma-Aminobutyric Acid Type-A Receptors Using Novel Machine-Learning-Based SVM and GBDT Approaches
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• WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest
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  Udgivet: (2018)