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SVM-based classification of class C GPCRs from alignment-free physicochemical transformations of their sequences

Autor
König, C.; Cruz, R.; Alquezar, R.; Vellido, A.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
17th International Conference on Image Analysis and Processing
Any de l'edició
2013
Data de presentació
2013-09-09
Llibre d'actes
New Trends in Image Analysis and Processing - ICIAP 2013
Pàgina inicial
336
Pàgina final
343
Editor
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-41190-8_36 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/23281 Obrir en finestra nova
URL
http://link.springer.com/chapter/10.1007%2F978-3-642-41190-8_36 Obrir en finestra nova
Resum
G protein-coupled receptors (GPCRs) have a key function in regulating the function of cells due to their ability to transmit extracelullar signals. Given that the 3D structure and the functionality of most GPCRs is unknown, there is a need to construct robust classification models based on the analysis of their amino acid sequences for protein homology detection. In this paper, we describe the supervised classification of the different subtypes of class C GPCRs using support vector machines (SVM...
Citació
König, C. [et al.]. SVM-based classification of class C GPCRs from alignment-free physicochemical transformations of their sequences. A: International Conference on Image Analysis and Processing. "New Trends in Image Analysis and Processing - ICIAP 2013". Naples: Springer Berlin Heidelberg, 2013, p. 336-343.
Paraules clau
G-Protein coupled receptors, Homology, Pharmaco-proteomics, Supervised learning, Support vector machines, Transformation
Grup de recerca
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
SOCO - Soft Computing

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