Knowledge Discovery in Spectral Data by Means of Complex Networks

Zanin, Massimiliano and Papo, David and González Solis, Jose Luis and Martínez Espinosa, Juan Carlos and Frausto-Reyes, Claudio and Palomares Anda, Pascual and Sevilla-Escoboza, Ricardo and Jaimes-Reategui, Rider and Boccaletti, Stefano and Menasalvas Ruiz, Ernestina and Sousa, Pedro (2013). Knowledge Discovery in Spectral Data by Means of Complex Networks. "Metabolites", v. 3 (n. 1); pp. 155-167. ISSN 2218-1989. https://doi.org/10.3390/metabo3010155.

Description

Title: Knowledge Discovery in Spectral Data by Means of Complex Networks
Author/s:
  • Zanin, Massimiliano
  • Papo, David
  • González Solis, Jose Luis
  • Martínez Espinosa, Juan Carlos
  • Frausto-Reyes, Claudio
  • Palomares Anda, Pascual
  • Sevilla-Escoboza, Ricardo
  • Jaimes-Reategui, Rider
  • Boccaletti, Stefano
  • Menasalvas Ruiz, Ernestina
  • Sousa, Pedro
Item Type: Article
Título de Revista/Publicación: Metabolites
Date: March 2013
ISSN: 2218-1989
Volume: 3
Subjects:
Faculty: Centro de Tecnología Biomédica (CTB) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled) subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

More information

Item ID: 19173
DC Identifier: http://oa.upm.es/19173/
OAI Identifier: oai:oa.upm.es:19173
DOI: 10.3390/metabo3010155
Official URL: http://www.mdpi.com/2218-1989/3/1/155
Deposited by: Memoria Investigacion
Deposited on: 16 Oct 2013 18:37
Last Modified: 21 Apr 2016 17:24
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