Metabolic Network Completion. Compute minimal completions to your draft network with reactions from a repair network.
Requires Python >= 3.6
Required packages (starting from version 2.0 of the package):
You can install Meneco by running:
python setup.py install
Usage from console
Typical usage is:
meneco -d draftnetwork.sbml -s seeds.sbml -t targets.sbml -r repairnetwork.sbml
For more options you can ask for help as follows:
meneco --h usage: meneco.py [-h] -d DRAFTNET -s SEEDS -t TARGETS [-r REPAIRNET] [--enumerate] optional arguments: -h, --help show this help message and exit -d DRAFTNET, --draftnet DRAFTNET metabolic network in SBML format -s SEEDS, --seeds SEEDS seeds in SBML format -t TARGETS, --targets TARGETS targets in SBML format -r REPAIRNET, --repairnet REPAIRNET perform network completion using REPAIRNET a metabolic network in SBML format --enumerate enumerate all minimal completions
Calling Meneco from a python script
You can use meneco from python by calling the command run_meneco() with the paths of files as input arguments and a boolean value for the enumeration (TRUE for the enumeration, else FALSE) :
from meneco import meneco run_meneco("draftnetwork.sbml", "seeds.sbml", "targets.sbml", "repairnetwork.sbml", TRUE)
The output will be the set of unproducible targets, reconstructable targets, a dictionnary of essentials reactions for each target, the set of reactions belonging to the intersection of solutions, the set of reactions belonging to the union of solutions and a list of lists corresponding to the reactions for each solution.
For a guided example, see a demonstration IPython Notebook.
Please cite the following paper when using Meneco:
S. Prigent et al., “Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks,” PLOS Computational Biology, vol. 13, no. 1, p. e1005276, Jan. 2017.
The concepts underlying Meneco is described in this paper:
T. Schaub and S. Thiele, “Metabolic network expansion with answer set programming,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, vol. 5649 LNCS, pp. 312–326.
A first application of the method was presented in:
G. Collet et al., “Extending the Metabolic Network of Ectocarpus Siliculosus Using Answer Set Programming,” in LPNMR 2013: Logic Programming and Nonmonotonic Reasoning, 2013, pp. 245–256.
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