rezacsedu/Drug-Drug-Interaction-Prediction

Drug-Drug Interaction Prediction Based on Knowledge Graph Embeddings and Convolutional-LSTM Network

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This project helps pharmacology researchers and drug discovery scientists predict potential drug-drug interactions (DDIs). It takes information from drug databases like DrugBank, PharmGKB, and KEGG, processes it into a feature-rich representation, and then uses these features to identify unforeseen negative interactions between drugs. The result is a list of predicted DDIs that can inform drug development and patient safety.

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Use this if you are a pharmacology researcher or drug discovery scientist looking to systematically predict potential drug-drug interactions using existing knowledge graph data.

Not ideal if you are a clinical practitioner seeking real-time patient-specific DDI alerts, as this is a research tool for drug discovery.

drug-discovery pharmacology drug-safety bioinformatics medicinal-chemistry
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 20 / 25

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Last pushed

Oct 09, 2019

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