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gMCS: fast computation of genetic minimal cut sets in large networks.
Apaolaza, Iñigo; Valcarcel, Luis Vitores; Planes, Francisco J.
Afiliación
  • Apaolaza I; Department of Biomedical Engineering and Sciences, Tecnun School of Engineering, University of Navarra, San Sebastián, Spain.
  • Valcarcel LV; Department of Biomedical Engineering and Sciences, Tecnun School of Engineering, University of Navarra, San Sebastián, Spain.
  • Planes FJ; Centro de Investigación Médica Aplicada (CIMA), University of Navarra, Programa de Oncohematología, Pamplona, Spain.
Bioinformatics ; 35(3): 535-537, 2019 02 01.
Article en En | MEDLINE | ID: mdl-30052768
ABSTRACT
Motivation The identification of minimal gene knockout strategies to engineer metabolic systems constitutes one of the most relevant applications of the COnstraint-Based Reconstruction and Analysis (COBRA) framework. In the last years, the minimal cut sets (MCSs) approach has emerged as a promising tool to carry out this task. However, MCSs define reaction knockout strategies, which are not necessarily transformed into feasible strategies at the gene level.

Results:

We present a more general, easy-to-use and efficient computational implementation of a previously published algorithm to calculate MCSs to the gene level (gMCSs). Our tool was compared with existing methods in order to calculate essential genes and synthetic lethals in metabolic networks of different complexity, showing a significant reduction in model size and computation time. Availability and implementation gMCS is publicly and freely available under GNU license in the COBRA toolbox (https//github.com/opencobra/cobratoolbox/tree/master/src/analysis/gMCS). Supplementary information Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Biología Computacional / Redes y Vías Metabólicas Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Biología Computacional / Redes y Vías Metabólicas Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: España