Manifold learning visualization of metabotropic glutamate receptors
作者： Jesús Giraldo Arjonilla , Martha Ivón Cárdenas Domínguez , Alfredo Vellido Alcacena
DOI: 10.3233/978-1-61499-452-7-269
关键词: Amino acid 、 G protein-coupled receptor 、 Receptor 、 Biology 、 Class C GPCR 、 Neuroscience 、 Lack of knowledge 、 Nonlinear dimensionality reduction 、 Metabotropic glutamate receptor 、 Visualization
摘要: G-Protein-Coupled Receptors (GPCRs) are cell membrane proteins with a key role in biological processes. GPCRs of class C, particular, great interest pharmacology. The lack knowledge about their 3-D structures means they must be investigated through 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 (mGluR), subtype C GPCRs. Different versions probabilistic manifold learning model employed comparatively sub-group and visualize them transformations
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