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Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors

Author
Koenig, C.; Cardenas, M.; Giraldo, J.; Alquezar, R.; Vellido, A.
Type of activity
Journal article
Journal
BMC bioinformatics
Date of publication
2015-09-29
Volume
16:314
First page
1
Last page
14
DOI
https://doi.org/10.1186/s12859-015-0731-9 Open in new window
Project funding
Adquisición de conocimiento en farmacoproteomica mediante métodos avanzados de inteligencia artificial (KAPPA AIM)
Repository
http://hdl.handle.net/2117/78745 Open in new window
URL
http://www.biomedcentral.com/1471-2105/16/314/ Open in new window
Abstract
Background: The characterization of proteins in families and subfamilies, at different levels, entails the definition and use of class labels. When the adscription of a protein to a family is uncertain, or even wrong, this becomes an instance of what has come to be known as a label noise problem. Label noise has a potentially negative effect on any quantitative analysis of proteins that depends on label information. This study investigates class C of G protein-coupled receptors, which are cell m...
Citation
Koenig, C., Cardenas, M., Giraldo, J., Alquezar, R., Vellido, A. Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors. "BMC bioinformatics", 29 Setembre 2015, vol. 16:314, p. 1-14.
Keywords
G Protein-coupled receptors, Label noise, Phylogenetic trees, Support vector machines
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
SOCO - Soft Computing
VIS - Artificial Vision and Intelligent Systems

Participants

Attachments