Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0
Abstract
COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation 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 optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods.
Keywords
Cite
@article{arxiv.1710.04038,
title = {Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0},
author = {Laurent Heirendt and Sylvain Arreckx and Thomas Pfau and Sebastián N. Mendoza and Anne Richelle and Almut Heinken and Hulda S. Haraldsdóttir and Jacek Wachowiak and Sarah M. Keating and Vanja Vlasov and Stefania Magnusdóttir and Chiam Yu Ng and German Preciat and Alise Žagare and Siu H. J. Chan and Maike K. Aurich and Catherine M. Clancy and Jennifer Modamio and John T. Sauls and Alberto Noronha and Aarash Bordbar and Benjamin Cousins and Diana C. El Assal and Luis V. Valcarcel and Iñigo Apaolaza and Susan Ghaderi and Masoud Ahookhosh and Marouen Ben Guebila and Andrejs Kostromins and Nicolas Sompairac and Hoai M. Le and Ding Ma and Yuekai Sun and Lin Wang and James T. Yurkovich and Miguel A. P. Oliveira and Phan T. Vuong and Lemmer P. El Assal and Inna Kuperstein and Andrei Zinovyev and H. Scott Hinton and William A. Bryant and Francisco J. Aragón Artacho and Francisco J. Planes and Egils Stalidzans and Alejandro Maass and Santosh Vempala and Michael Hucka and Michael A. Saunders and Costas D. Maranas and Nathan E. Lewis and Thomas Sauter and Bernhard Ø. Palsson and Ines Thiele and Ronan M. T. Fleming},
journal= {arXiv preprint arXiv:1710.04038},
year = {2018}
}