cobamp - pathway analysis methods for genome-scale metabolic models
Project description
CoBAMP
CoBAMP (Constraint-Based Analysis of Metabolic Pathways) is a Python package containing pathway analysis methods for use with constraint-based metabolic models. The main purpose is to provide a framework that is both modular and flexible enough to be integrated in other packages (such as cobrapy, framed or cameo) that already implement generic data structures for metabolic models.
A (MI)LP solver is required for most of the methods. Current methods are implemented using CPLEX as a solver, although future versions will use a unifying solver platform, such as optlang.
- Current methods include:
Elementary flux modes: K-Shortest algorithm
Minimal cut sets: MCSEnumerator approach
Elementary flux patterns: K-Shortest algorithm
Documentation
Instalation from PyPI (stable releases)
pip install cobamp
Instalation from github (latest development release)
pip install https://github.com/skapur/pyCoBAMP/archive/master.zip
Credits and License
Developed at the Centre of Biological Engineering, University of Minho
Released under the GNU Public License (version 3.0).
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