Abstract
The world of pharmacology is becoming increasingly dependent on the advances in the fields of genomics and proteomics. This dependency brings about the challenge of finding robust methods to analyze the complex data they generate. In this brief paper, we focus on the analysis of a specific type of proteins, the G protein-couple receptors, which are the target for over 15% of current drugs. We describe a kernel method of the manifold learning family for the analysis and intuitive visualization of their protein amino acid symbolic sequences. This method is shown to reveal the grouping structure of the sequences in a way that closely resembles the corresponding phylogenetic trees.
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Cárdenas, M.I., Vellido, A., Olier, I., Rovira, X., Giraldo, J. (2012). Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree. In: Biganzoli, E., Vellido, A., Ambrogi, F., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2011. Lecture Notes in Computer Science(), vol 7548. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35686-5_12
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DOI: https://doi.org/10.1007/978-3-642-35686-5_12
Publisher Name: Springer, Berlin, Heidelberg
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