AstraZeneca/awesome-drug-pair-scoring

Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

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This project helps researchers and scientists understand and evaluate different methods for predicting how drug pairs interact, which is crucial for identifying potential side effects or beneficial synergies. It provides a structured collection of research papers and models related to drug pair scoring. The target users are computational biologists, pharmacologists, and drug discovery researchers.

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Use this if you need to research existing deep learning approaches for predicting drug-drug interactions or drug synergy, and want to explore various model architectures and datasets.

Not ideal if you are looking for a ready-to-use software tool or API to perform drug pair scoring directly, as this is a curated list of research readings.

drug-discovery pharmacology drug-interaction-prediction synergy-research computational-biology
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Maturity 16 / 25
Community 15 / 25

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Apache-2.0

Last pushed

Aug 07, 2022

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