Predict missing edges in a knowledge graph
Project description
Documentation for the EdgePrediction library
This repository contains a Python implementation of the knowledge graph edge prediction algorithm described in Bean et al. 2017, and the input drug knowledge graph used in that paper. The algorithm is a general binary classifier that leans a model to predict new members of a given class within the training data.
Install
The package is available through pip:
pip install edgeprediction
Contents:
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- Dependencies list
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Initial setup
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Input data format
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Load data
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Prepare to run prediction algorithm
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Run prediction algorithm
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Acknowledgements
This work is funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London.
The publicly available drug data as used in Bean et al. 2017 was collected from DrugBank (www.drugbank.ca) and SIDER (http://sideeffects.embl.de).
Documentation and testing
Documentation is built with sphinx from docs_templates with sphinx>=v3.4.3
sphinx-build -M markdown ./ ../docs
Testing with pytest
python -m pytest tests
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