Por favor, use este identificador para citar o enlazar este ítem: https://doi.org/10.1093/bioinformatics/btad356

Título: On the representativeness and stability of a set of EFMs
Fecha de publicación: 30-may-2023
Editorial: Oxford Academic
Cita bibliográfica: Bioinformatics, 2023, 39(6), btad356
ISSN: 1367-4811
Resumen: Motivation: Elementary flux modes are a well-known tool for analyzing metabolic networks. The whole set of elementary flux modes (EFMs) cannot be computed in most genome-scale networks due to their large cardinality. Therefore, different methods have been proposed to compute a smaller subset of EFMs that can be used for studying the structure of the network. These latter methods pose the problem of studying the representativeness of the calculated subset. In this article, we present a methodology to tackle this problem. Results: We have introduced the concept of stability for a particular network parameter and its relation to the representativeness of the EFM extraction method studied. We have also defined several metrics to study and compare the EFM biases. We have applied these techniques to compare the relative behavior of previously proposed methods in two case studies. Furthermore, we have presented a new method for the EFM computation (PiEFM), which is more stable (less biased) than previous ones, has suitable representativeness measures, and exhibits better variability in the extracted EFMs
Autor/es principal/es: Guil Asensio, Francisco
Hidalgo Céspedes, José F.
García Carrasco, José Manuel
Facultad/Departamentos/Servicios: Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Ingeniería y Tecnología de Computadores
URI: http://hdl.handle.net/10201/139003
DOI: https://doi.org/10.1093/bioinformatics/btad356
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 10
Derechos: info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Descripción: ©2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Published, version of a Published Work that appeared in final form in Bioinformatics. To access the final edited and published work see https://doi.org/10.1093/bioinformatics/btad356
Aparece en las colecciones:Artículos: Ingeniería y Tecnología de Computadores

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