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Enabling network inference methods to handle missing data and outliers

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Enabling network inference methods to handle missing data and outliers

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Abel Folch-Fortuny; Fernández Villaverde, A.; Ferrer Riquelme, AJ.; Rodríguez Banga, J. (2015). Enabling network inference methods to handle missing data and outliers. BMC Bioinformatics. 16(283):1-12. doi:10.1186/s12859-015-0717-7

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Título: Enabling network inference methods to handle missing data and outliers
Autor:
Entidad UPV: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Fecha difusión:
Resumen:
[EN] Background: The inference of complex networks from data is a challenging problem in biological sciences, as well as in a wide range of disciplines such as chemistry, technology, economics, or sociology. The quantity ...[+]
Palabras clave: Network inference , Missing data , Outlier detection , Projection to latent structures , Trimmed scores regression , Information theory , Mutual information
Derechos de uso: Reconocimiento (by)
Fuente:
BMC Bioinformatics. (issn: 1471-2105 )
DOI: 10.1186/s12859-015-0717-7
Editorial:
BioMed Central
Versión del editor: https://dx.doi.org/10.1186/s12859-015-0717-7
Código del Proyecto: info:eu-repo/grantAgreement/EC/FP7/289434
Descripción: © 2015 Folch-Fortuny et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Patrocinador:
Spanish Ministry of Science and Innovation
European Union through project BioPreDyn (FP7-KBBE) 289434
European Union DPI2011-28112-C04-02
European Union DPI2011-28112-C04-03
Xunta de Galicia through an I2C postdoctoral fellowship I2C ED481B 2014/133-0
SynBioFactory DPI2014-55276-C5-1-R
SynBioFactory DPI2014-55276-C5-2-R
Tipo: Artículo

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