This repository contains a python implementation of the BowTieBuilder Algorithm.
The recommended python version is at ./.python-version, which is currently 3.13. All required dependencies are available at pyproject.toml.
Implemented into the Signaling Pathway Reconstruction Streamliner (SPRAS).
Command Line Test:
python btb.py --edges ./input/edges.txt --sources ./input/source.txt --targets ./input/target.txt --output ./output/output.txt
The sources and targets file is a newline-delimited list of sources and targets present in the edges, and the edges file is a tab-delimited three column (the last column, weight, between 0.0 and 1.0, is optional) file representing a directed interactome.
This outputs a directed subnetwork of the original input edges interactome.
Example Output:
(This was generated using ./vis.ipynb - see its instructions on how to reproduce this figure.)
The original paper for BowTieBuilder can be accessed here:
Supper, J., Spangenberg, L., Planatscher, H. et al. BowTieBuilder: modeling signal transduction pathways. BMC Syst Biol 3, 67 (2009). https://doi.org/10.1186/1752-0509-3-67
Available on DockerHub.
A simple pathway reconstruction algorithm that attempts to join sources and targets into a BowTie shape. The algorithm takes a network and 2 lists of nodes (source and target sets) as input. It outputs all edges in the network that are on the shortest paths from source to target sets.