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The extracellular N-terminal domain suffices to discriminate class C G Protein-Coupled Receptor subtypes from n-grams of their sequences.

, , , and . IJCNN, page 1-7. IEEE, (2015)

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Molecular Dynamics forecasting of transmembrane Regions in GPRCs by Recurrent Neural Networks., , and . BHI, page 1-4. IEEE, (2022)SVM-Based Classification of Class C GPCRs from Alignment-Free Physicochemical Transformations of Their Sequences., , , and . ICIAP Workshops, volume 8158 of Lecture Notes in Computer Science, page 336-343. Springer, (2013)The extracellular N-terminal domain suffices to discriminate class C G Protein-Coupled Receptor subtypes from n-grams of their sequences., , , and . IJCNN, page 1-7. IEEE, (2015)Analysis of class C G-protein coupled receptors using supervised classification methods.. Polytechnic University of Catalonia, Spain, (2018)A Deep Learning-Based Method for Uncovering GPCR Ligand-Induced Conformational States Using Interpretability Techniques., , and . IWBBIO (2), volume 13347 of Lecture Notes in Computer Science, page 275-287. Springer, (2022)Discovering Subtype Specific n-Gram Motifs in Class C GPCR N-Termini., , , and . CCIA, volume 300 of Frontiers in Artificial Intelligence and Applications, page 116-125. IOS Press, (2017)Topological Sequence Segments Discriminate Between Class C GPCR Subtypes., , , and . PACBB, volume 616 of Advances in Intelligent Systems and Computing, page 164-172. Springer, (2017)Exploratory Visualization of Misclassified GPCRs from their transformed unaligned sequences using manifold learning techniques., , , , and . IWBBIO, page 623-630. Copicentro Editorial, (2014)Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns., , , and . J. Integr. Bioinform., (2014)Misclassification of class C G-protein-coupled receptors as a label noise problem., , , and . ESANN, (2014)