G-Protein-Coupled Receptors (GPCRs) are cell membrane proteins with a key role in biological processes. GPCRs of class C, in particular, are of great interest in pharmacology. The lack of knowledge about their 3-D structures means they must be investigated through their primary amino acid sequences. Sequence visualization can help to explore the existing receptor sub-groupings at different partition levels. In this paper, we focus on Metabotropic Glutamate Receptors (mGluR), a subtype of class C GPCRs. Different versions of a probabilistic manifold learning model are employed to comparatively sub-group and visualize them through different transformations of their sequences.
CitationCárdenas, M.I., Vellido, A., Giraldo, J. Manifold learning visualization of metabotropic glutamate receptors. A: International Conference of the Catalan Association for Artificial Intelligence. "Artificial Intelligence Research and Development: Proceedings of the 17th International Conference of the Catalan Association for Artificial Intelligence, Barcelona, Catalonia, Spain, October 22-24, 2014". Barcelona: IOS Press, 2014, p. 269-272.
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