Papers with DrugBank

2 papers
Bridging Distance and Spectral Positional Encodings via Anchor-Based Diffusion Geometry Approximation (2026.acl-long)

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Challenge: Molecular graph learning benefits from positional signals that capture local neighborhoods and global topology.
Approach: They propose to use anchor-based distance encodings to approximate diffusion geometry.
Outcome: The proposed model outperforms models without positional encodings on DrugBank with a shared GNP-based DDI backbone.
Learning to Describe for Predicting Zero-shot Drug-Drug Interactions (2023.emnlp-main)

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Challenge: Existing computational methods for DDI prediction fail to capture interactions for new drugs due to the lack of knowledge.
Approach: They propose a problem setup as zero-shot DDI prediction that deals with the case of new drugs by using textual information from online databases.
Outcome: The proposed method improves on several settings including zero-shot and few-shot DDI prediction and the selected texts are semantically relevant.

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