• Stars
    star
    247
  • Rank 164,117 (Top 4 %)
  • Language
    MATLAB
  • License
    Other
  • Created about 12 years ago
  • Updated about 2 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:

The COBRA Toolbox
COnstraint-Based Reconstruction and Analysis Toolbox

All continuous integration builds
Ratio of the number of inefficient code lines and the total number of lines of code (in percent). A: 0-3%, B: 3-6%, C: 6-9%, D: 9-12%, E: 12-15%, F: > 15%.

System Requirements and Solver Installation

warning Please follow this guide in order to configure your system properly.

warning Please make sure you install a compatible solver. Check the compatibility here.

You may install TOMLAB, IBM ILOG CPLEX, GUROBI, or MOSEK by following these detailed instructions.

Installation

  1. Download this repository (the folder ./cobratoolbox/ will be created). You can clone the repository using:

    $ git clone --depth=1 https://github.com/opencobra/cobratoolbox.git cobratoolbox

    warning Please note the --depth=1 in the clone command. Run this command in Terminal (on macOS and linux) or in Git Bash (on windows) - not in matlab. Although not recommended, you can download the repository as a compressed archive.

  2. Change to the folder cobratoolbox/ and run from matlab

    >> initCobraToolbox

Tutorials, Documentation, and Support

  • Consult all tutorials in the section . All tutorials can be run from the /tutorials directory.
  • All functions are documented in the .
  • If you need support, please feel free to post your question in our .
  • Answers to Frequently Asked Questions (FAQ) are here.

How to contribute

thumbsup tada First off, thanks for taking the time to contribute to The COBRA Toolbox! tada thumbsup

devTools

You can install the MATLAB.devTools from within MATLAB by typing:

>> installDevTools()

bulb Check out MATLAB.devTools - and contribute the smart way! The official documentation is here.

thumbsup Contribute to the opencobra/cobratoolbox repository by following these instructions:

>> contribute('opencobra/cobratoolbox');

thumbsup Contribute to the opencobra/COBRA.tutorials repository by following these instructions:

>> contribute('opencobra/COBRA.tutorials');
  • Please follow the Style Guide.
  • More information on writing a test is here and a template is here.
  • More information on formatting the documentation is here
  • A guide for reporting an issue is here.

If you want to use git via the command line interface and need help, this guide or the official GitHub guide come in handy.

How to cite the COBRA Toolbox

When citing the COBRA Toolbox, it is important to cite the original paper where an algorithm was first reported, as well as its implementation in the COBRA Toolbox. This is important, because the objective of the COBRA Toolbox is to amalgamate and integrate the functionality of a wide range of COBRA algorithms and this will be undermined if contributors of new algorithms do not get their fair share of citations. The following is one example how to approach this within the methods section of a paper (not the supplemental material please):

To generate a context-specific model the FASTCORE algorithm [1], implemented in The COBRA Toolbox v3.0 [2], was employed.

[1] = Vlassis N, Pacheco MP, Sauter T (2014) Fast Reconstruction of Compact Context-Specific Metabolic Network Models. PLoS Comput Biol 10(1): e1003424.
[2] Laurent Heirendt & Sylvain Arreckx, Thomas Pfau, Sebastian N. Mendoza, Anne Richelle, Almut Heinken, Hulda S. Haraldsdottir, Jacek Wachowiak, Sarah M. Keating, Vanja Vlasov, Stefania Magnusdottir, Chiam Yu Ng, German Preciat, Alise Zagare, Siu H.J. Chan, Maike K. Aurich, Catherine M. Clancy, Jennifer Modamio, John T. Sauls, Alberto Noronha, Aarash Bordbar, Benjamin Cousins, Diana C. El Assal, Luis V. Valcarcel, Inigo Apaolaza, Susan Ghaderi, Masoud Ahookhosh, Marouen Ben Guebila, Andrejs Kostromins, Nicolas Sompairac, Hoai M. Le, Ding Ma, Yuekai Sun, Lin Wang, James T. Yurkovich, Miguel A.P. Oliveira, Phan T. Vuong, Lemmer P. El Assal, Inna Kuperstein, Andrei Zinovyev, H. Scott Hinton, William A. Bryant, Francisco J. Aragon Artacho, Francisco J. Planes, Egils Stalidzans, Alejandro Maass, Santosh Vempala, Michael Hucka, Michael A. Saunders, Costas D. Maranas, Nathan E. Lewis, Thomas Sauter, Bernhard ร˜. Palsson, Ines Thiele, Ronan M.T. Fleming, Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0, Nature Protocols, volume 14, pages 639โ€“702, 2019 doi.org/10.1038/s41596-018-0098-2.

Binaries and Compatibility

warning Please make sure you install a compatible solver. Check the compatibility here.

For convenience, we provide glpk_mex and libSBML-5.17+ in /external.

Binaries for these libraries are provided in a submodule for Mac OS X 10.6 or later (64-bit), GNU/Linux Ubuntu 14.0+ (64-bit), and Microsoft Windows 7+ (64-bit). For unsupported OS, please refer to their respective building instructions (glpk_mex, libSBML).

Read more on the compatibility with SBML-FBCv2 here.

Disclaimer

The software provided by the openCOBRA Project is distributed under the GNU GPLv3 or later. However, this software is designed for scientific research and as such may contain algorithms that are associated with patents in the U.S. and abroad. If the user so chooses to use the software provided by the openCOBRA project for commercial endeavors then it is solely the userโ€™s responsibility to license any patents that may exist and respond in full to any legal actions taken by the patent holder.

More Repositories

1

cobrapy

COBRApy is a package for constraint-based modeling of metabolic networks.
Python
413
star
2

optlang

optlang - sympy based mathematical programming language
Python
215
star
3

memote

memote โ€“ the genome-scale metabolic model test suite
HTML
120
star
4

COBRA.jl

High-level, high-performance, constraint-based reconstruction and analysis in Julia
Julia
61
star
5

MATLAB.devTools

MATLAB Development Tools
MATLAB
27
star
6

Medusa

Analysis of ensembles of metabolic network reconstructions
Python
20
star
7

COBRA.tutorials

Repository of tutorials for The COBRA Toolbox
MATLAB
18
star
8

m_model_collection

A collection of M models downloaded from published studies
Jupyter Notebook
14
star
9

driven

Data-Driven Constraint-based analysis
Python
13
star
10

MASS-Toolbox

Mass Action Stoichiometric Simulation (MASS) Toolbox
Mathematica
11
star
11

COBRA.papers

Repository for scripts related to reproducing the results of an individual publication
MATLAB
8
star
12

cobra-component-models

Provide SQLAlchemy ORM and pydantic data models for SQL storage and serialization of COBRA components such as reactions, compounds, and compartments.
Python
3
star
13

memote-docker

Easily use the memote command line interface from a docker container.
Shell
3
star
14

cookiecutter-memote

A cookiecuttter template for memote model repositories
Python
2
star
15

cookiecutter-python-package

Extensive cookiecutter template for openCOBRA Python packages.
Python
2
star
16

schema

xml/rdf schemas for annotating cobra models
2
star
17

cobrapy_shim

Shim for the COBRA toolbox to call cobrapy functions
Python
1
star
18

cobrapy-bigg-client

Python
1
star
19

cobrapy-website

HTML
1
star
20

ctf

Chemical table files for constraint-based modelling
1
star
21

COBRA.binary

Linux, Windows and Mac binaries maintained by the constraint-based reconstruction and analysis community
MATLAB
1
star