{"id":34038530,"url":"https://github.com/drug2ways/drug2ways","last_synced_at":"2026-04-06T02:01:35.465Z","repository":{"id":46682206,"uuid":"267315762","full_name":"drug2ways/drug2ways","owner":"drug2ways","description":"A Python package for drug discovery by analyzing causal paths on multiscale 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align=\"center\"\u003e\n  \u003ca href=\"https://drug2ways.readthedocs.io/en/latest\"\u003e\n     \u003cimg src=\"docs/source/meta/logo1.jpg\" height=\"300\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003ch1 align=\"center\"\u003e\n  drug2ways\n\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://travis-ci.com/drug2ways/drug2ways\"\u003e\n    \u003cimg src=\"https://travis-ci.com/drug2ways/drug2ways.svg?branch=master\"\n         alt=\"Travis CI\"\u003e\n  \u003c/a\u003e\n\n  \u003ca href='https://opensource.org/licenses/Apache-2.0'\u003e\n    \u003cimg src='https://img.shields.io/badge/License-Apache%202.0-blue.svg' alt='License'/\u003e\n  \u003c/a\u003e\n\n  \u003ca href=\"https://zenodo.org/badge/latestdoi/267315762\"\u003e\n    \u003cimg src=\"https://zenodo.org/badge/267315762.svg\" alt=\"DOI\"\u003e\n  \u003c/a\u003e\n\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003cb\u003eDrug2ways\u003c/b\u003e is a Python package for reasoning over paths on biological networks for drug discovery\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"#quickstart\"\u003eQuickstart\u003c/a\u003e •\n  \u003ca href=\"#applications\"\u003eApplications\u003c/a\u003e •\n  \u003ca href=\"#installation\"\u003eInstallation\u003c/a\u003e\n\u003c/p\u003e\n\n\n## Quickstart\nDrug2ways supports generic network formats such as JSON, CSV, GraphML, or GML. Check out [drug2ways's documentation here](https://drug2ways.readthedocs.io/en/latest). Ideally, the network should contain three different types of nodes\nrepresenting drugs, proteins, and indications/phenotypes. The hypothesis underlying this software is that by reasoning\nover a multitude of possible paths between a given drug and indication, the drug regulates the indication in the\ndirection of the signs of the most frequently occurring paths (i.e., majority rule). In other words, we assume that a\ndrug has a greater likelihood of interacting with its target, and its target with intermediate nodes, to modulate a\npathological phenotype as the number of possible paths connecting a drug to the phenotype increases. Based on this\nhypothesis, this software can be applied for different applications outlined in the next section.\n\n### Citation\nIf you use drug2ways for your research please cite our [paper](https://doi.org/10.1371/journal.pcbi.1008464): \n\n\u003e Daniel Rivas-Barragan, Sarah Mubeen, Francesc Guim-Bernat,Martin Hofmann-Apitius, and Daniel Domingo-Fernández (2020).\nDrug2ways: Reasoning over causal paths in biological networks for drug discovery. *PLOS Computational Biology* 16(12): e1008464;  https://doi.org/10.1371/journal.pcbi.1008464\n\n## Applications\nDrug2ways can be applied for three different applications:\n\n**Scripts and real examples**: https://github.com/drug2ways/drug2ways/tree/master/examples\n\n### 1. Identifying candidate drugs\nThe following command of the command line interface (CLI) of drug2ways enables candidate drug identification. The\nminimum required input are the path to the network and its format, a path to the nodes considered as drugs and the\nones considered as conditions/phenotypes. Finally, the maximum length allowed for a given path (i.e., lmax). Type\n\"python -m drug2ways explore --help\" to see other optional arguments.\n\n```python\npython -m drug2ways explore \\\n       --graph=\u003cpath-to-graph\u003e \\\n       --fmt=\u003cformat\u003e \\\n       --sources=\u003csources\u003e \\\n       --targets=\u003ctargets\u003e \\\n       --lmax=\u003clmax\u003e\n```\n\n### 2. Optimization of drugs' effects\nThe following command of the CLI of drug2ways enables searching drugs that not only target a given disease but also\nactivate/inhibit a set of phenotypes. This method requires the same arguments as the previous explore functionality\nbut the target file requires an additional second column where the desired effect on the node (e.g., 'node1,activate')\nis specified. See the examples directory for more information.\n\n```python\npython -m drug2ways optimize \\\n       --graph=\u003cpath-to-graph\u003e \\\n       --fmt=\u003cformat\u003e \\\n       --sources=\u003csources\u003e \\\n       --targets=\u003ctargets\u003e \\ # Note that this file is slightly different than the other targets\n       --lmax=\u003clmax\u003e\n```\n\n### 3. Proposing combination therapies\nThe following command of the CLI of drug2ways enables the identification of candidate drugs for combination therapies.\nThe minimum required input are the path to the network and its format, a path to the nodes considered as drugs and the\nones considered as conditions/phenotypes. As with the optimization command, here again the target file requires an\nadditional second column specifying the desired effect on the node (e.g., 'node1,activate'). Furthermore, the maximum\nlength allowed for a given path (i.e., lmax) and the possible number of combinations of drugs must be provided. Type\n\"python -m drug2ways combine --help\" to see other optional arguments.\n\n```python\npython -m drug2ways combine \\\n       --graph=\u003cpath-to-graph\u003e \\\n       --fmt=\u003cformat\u003e \\\n       --sources=\u003csources\u003e \\\n       --targets=\u003ctargets\u003e \\\n       --lmax=\u003clmax\u003e \\\n       --combination-length=\u003cnumber\u003e\n```\n\n## Installation\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://drug2ways.readthedocs.io/en/latest/\"\u003e\n    \u003cimg src=\"http://readthedocs.org/projects/drug2ways/badge/?version=latest\"\n         alt=\"Documentation\"\u003e\n  \u003c/a\u003e\n\n  \u003cimg src='https://img.shields.io/pypi/pyversions/drug2ways.svg' alt='Stable Supported Python Versions'/\u003e\n  \n  \u003ca href=\"https://pypi.python.org/pypi/drug2ways\"\u003e\n    \u003cimg src=\"https://img.shields.io/pypi/pyversions/drug2ways.svg\"\n         alt=\"PyPi\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\nThe latest stable code can be installed from [PyPI](https://pypi.python.org/pypi/drug2ways) with:\n\n```python\npython -m pip install drug2ways\n```\n\nThe most recent code can be installed from the source on [GitHub](https://github.com/drug2ways/drug2ways) with:\n\n```python\npython -m pip install git+https://github.com/drug2ways/drug2ways.git\n```\n\nFor developers, the repository can be cloned from [GitHub](https://github.com/drug2ways/drug2ways) and installed in\neditable mode with:\n\n```python\ngit clone https://github.com/drug2ways/drug2ways.git\ncd drug2ways\npython -m pip install -e .\n```\n\n## Requirements\n```python\nclick==7.1.1\ntqdm==4.47.0\nnetworkx\u003e=2.1\npandas==1.0.3\nnetworkx\u003e=2.4\nnumpy\nscipy\nstatsmodels\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdrug2ways%2Fdrug2ways","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdrug2ways%2Fdrug2ways","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdrug2ways%2Fdrug2ways/lists"}