Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

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Título: Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
Autor/es: Heirendt, Laurent | Arreckx, Sylvain | Pfau, Thomas | Mendoza, Sebastián N. | Richelle, Anne | Heinken, Almut | Haraldsdóttir, Hulda S. | Wachowiak, Jacek | Keating, Sarah M. | Vlasov, Vanja | Magnusdóttir, Stefania | Ng, Chiam Yu | Preciat, German | Žagare, Alise | Chan, Siu H.J. | Aurich, Maike K. | Clancy, Catherine M. | Modamio, Jennifer | Sauls, John T. | Noronha, Alberto | Bordbar, Aarash | Cousins, Benjamin | El Assal, Diana C. | Valcarcel, Luis V. | Apaolaza, Iñigo | Ghaderi, Susan | Ahookhosh, Masoud | Ben Guebila, Marouen | Kostromins, Andrejs | Sompairac, Nicolas | Le, Hoai M. | Ma, Ding | Sun, Yuekai | Wang, Lin | Yurkovich, James T. | Oliveira, Miguel A.P. | Vuong, Phan T. | El Assal, Lemmer P. | Kuperstein, Inna | Zinovyev, Andrei | Hinton, H. Scott | Bryant, William A. | Aragón Artacho, Francisco Javier | Planes, Francisco J. | Stalidzans, Egils | Maass, Alejandro | Vempala, Santosh | Hucka, Michael | Saunders, Michael A. | Maranas, Costas D. | Lewis, Nathan E. | Sauter, Thomas | Palsson, Bernhard Ø. | Thiele, Ines | Fleming, Ronan M.T.
Grupo/s de investigación o GITE: Laboratorio de Optimización (LOPT)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Matemáticas
Palabras clave: Constraint-based reconstruction and analysis (COBRA) | Biochemical constraint-based models
Área/s de conocimiento: Estadística e Investigación Operativa
Fecha de publicación: 20-feb-2019
Editor: Springer Nature
Cita bibliográfica: Nature Protocols. 2019, 14: 639-702. doi:10.1038/s41596-018-0098-2
Resumen: Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.
Patrocinador/es: This study was funded by the National Centre of Excellence in Research (NCER) on Parkinson’s disease, the U.S. Department of Energy, Offices of Advanced Scientific Computing Research and the Biological and Environmental Research as part of the Scientific Discovery Through Advanced Computing program, grant no. DE-SC0010429. This project also received funding from the European Union’s HORIZON 2020 Research and Innovation Programme under grant agreement no. 668738 and the Luxembourg National Research Fund (FNR) ATTRACT program (FNR/A12/01) and OPEN (FNR/O16/11402054) grants. N.E.L. was supported by NIGMS (R35 GM119850) and the Novo Nordisk Foundation (NNF10CC1016517). M.A.P.O. was supported by the Luxembourg National Research Fund (FNR) grant AFR/6669348. A.R. was supported by the Lilly Innovation Fellows Award. F.J.P. was supported by the Minister of Economy and Competitiveness of Spain (BIO2016-77998-R) and the ELKARTEK Programme of the Basque Government (KK-2016/00026). I.A. was supported by a Basque Government predoctoral grant (PRE_2016_2_0044). B.Ø.P. was supported by the Novo Nordisk Foundation through the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517).
URI: http://hdl.handle.net/10045/89710
ISSN: 1754-2189 (Print) | 1750-2799 (Online)
DOI: 10.1038/s41596-018-0098-2
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2019 Springer Nature Publishing AG
Revisión científica: si
Versión del editor: https://doi.org/10.1038/s41596-018-0098-2
Aparece en las colecciones:INV - LOPT - Artículos de Revistas
Investigaciones financiadas por la UE

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