Welcome to MetQuest's documentation!

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.

Citation

Ravikrishnan, A., Nasre, M. & Raman, K. Enumerating all possible biosynthetic pathways in metabolic networks. Sci. Rep. 8:9932 (2018).

Authors

Acknowledgments

Indian Institute of Technology Madras grant ERP/1314/004/RESF/KARH to Karthik Raman
INSPIRE fellowship, Department of Science and Technology, Government of India to Aarthi Ravikrishnan.
High Performance Computing Environment, P G Senapathy Centre for Computing Resources, IIT Madras
The work was partly supported by a research grantRB/18-19/CSE/002/INTI/BRAV from Intel Technology India Pvt Ltd to B Ravindran
Initiative for Biological Systems Engineering
Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI)

Installation

Use pip3 to install metquest from PyPI:

Via Python Package

pip3 install metquest

Direct installation

Install Python 3.4 or higher
Clone this repository to your computer using git or 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)

Required python packages

cobra >= 0.11.3
numpy >= 1.14.3
scipy
python-libsbml
networkx >= 2.1

Input

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

Running MetQuest

From command line

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>

From python console

>>>import metquest
>>>metquest.execute_all_codes()

When prompted, enter the path containing the folder with all the data files

Running examples

In the python console, type the following

>>>import metquest
>>>metquest.example.run_this_example()

This will run the example files.

TarsLi/metquest