TY - JOUR
T1 - Manifold learning visualization of Metabotropic glutamate receptors
AU - Cárdenas, Martha Ivón
AU - Vellido, Alfredo
AU - Giraldo, Jesús
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - data visualization
KW - G-Protein-Coupled Receptors
KW - Generative Topographic Mapping
KW - Metabotropic Glutamate Receptors
UR - http://www.scopus.com/inward/record.url?scp=84908150773&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-452-7-269
DO - 10.3233/978-1-61499-452-7-269
M3 - Article
AN - SCOPUS:84908150773
SN - 0922-6389
SP - 269
EP - 272
JO - Frontiers in Artificial Intelligence and Applications
JF - Frontiers in Artificial Intelligence and Applications
ER -