MetQuest is a dynamic programming based algorithm for identifying all possible pathways from metabolic networks between the source and the target metabolites. MetQuest requires the genome-scale metabolic reconstructions, set of seed, source and target metabolites and the pathway length cut-off. MetQuest is compatible with Python 3 and is OS-independent. An extensive documentation can be found here.
- Aarthi Ravikrishnan
- Meghana Nasre
- Karthik Raman
If you use MetQuest in your work, please cite
Ravikrishnan A., Nasre M., & Raman K. (2018) "Enumerating all possible biosynthetic pathways in metabolic networks" Scientific Reports 8:9932 doi:10.1038/s41598-018-28007-7
Use pip3 to install metquest from PyPI:
pip3 install metquest
- Install Python 3.4 or higher
- Clone this repository to your computer using
gitor download the repository and decompress it. - Navigate to the folder where metquest is downloaded and type
python3 setup.py install
(Elevated sudo rights may be required depending on the platform)
- cobra >= 0.11.3
- numpy >= 1.14.3
- scipy
- python-libsbml
- networkx >= 2.1
Folder whose structure is as shown:
mainfolder/
|-Example1/
| |-- SBML model(s) of metabolic networks # XML files of the metabolic networks(COBRA-compatible)
| |-- seed_mets.txt # Text file containing the seed metabolites separated by a newline
| |-- source_mets.txt # Text file containing the source metabolites separated by a newline
| |-- target_mets.txt # Text file containing the target metabolites separated by a newline
| |-- cutoff.txt # Text file containing the size cut-offs separated by a newline
|-Example2/
| ...
Kindly ensure that the SBML model has the field <model id> and the metabolites are prefixed with the model identifiers, for instance, if the model identifier is 'ecoli_core_model', and the seed metabolite is 'fum_c', the input text file should contain ecoli_core_model fum_c
MetQuest can be directly run from the terminal as
metquest.sh <path containing the input folder>
Navigate to the folder where metquest is installed and type
python3 execute_metquest.py <path containing the input folder>
>>>import metquest
>>>metquest.execute_all_codes()
When prompted, enter the path containing the folder with all the data files
In the python console, type the following
>>>import metquest
>>>metquest.example.run_this_example()
This will run the example files.
- Indian Institute of Technology Madras grant ERP/1314/004/RESF/KARH to KR
- INSPIRE fellowship, Department of Science and Technology, Government of India to AR
- Initiative for Biological Systems Engineering
- Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI)
