RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox is a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology
If you are using RAVEN in any scientific work, please cite: R. Agren, et. al, “The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum,” PLoS Comput. Biol., vol. 9, no. 3, p. e1002980, Mar. 2013..
RAVEN can be installed via cloning the Github repository as per below or by downloading and extracting one of the a zipped release. Please note that the releases do not always represent the most up to date version.
git clone [email protected]:SysBioChalmers/RAVEN.gitDon't forget to add raven to you matlab path. In matlab:
addpath(genpath('path/to/raven'))Required dependencies are currently libSBML and SBMLToolbox used for importing and exporting GEM models in SBML format. Install them and add to the matlab path:
addpath(genpath('path/to/libSBML'))
addpath(genpath('path/to/SBMLToolbox'))An optional but recommended dependency is Gurobi. Academic licenses are available here.
To install the gurobi matlab interface go to the gurobi installation directory and execute gurobi_setup as explained here. On Mac OS X in Matlab:
cd '/Library/gurobi651/mac64/matlab/'
gurobi_setupTo have matlab remember the above installations please save the current path to ’pathdef.m’ in your MATLAB startup directory. For instance on Mac OS X:
savepath '~/Documents/MATLAB/pathdef.m'Some tutorials highlighting basic RAVEN functionality can be found in the 'tutorial' folder in the installation directory.
For more information on software connected to Genome Scale models please visit the Systems Biology Github page. For information and publications by the Systems Biology department please visit SysBio.
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