Public articles linked to the same research event.
Journal of Chemical Information and Modeling This work proposes SSE-DDI, a framework that performs selective substructure encoding in molecular line graphs with chemical bonds as the fundamental representation units, complemented by an edge-fusion graph transformer and refined SMILES-derived Morgan-fingerprint similarity profiles; on DrugBank and Twosides under transductive and inductive settings it outperforms representative baselines across multiple metrics, with ablation and visualization analyses supporting the effectiveness of selective encoding and highlighting DDI-relevant molecular substructures.
This work proposes SSE-DDI, a framework that performs selective substructure encoding in molecular line graphs with chemical bonds as the fundamental representation units, complemented by an edge-fusion graph transformer and refined SMILES-derived Morgan-fingerprint similarity profiles; on DrugBank and Twosides under transductive and inductive settings it outperforms representative baselines across multiple metrics, with ablation and visualization analyses supporting the effectiveness of selective encoding and highlighting DDI-relevant molecular substructures.
This work proposes SSE-DDI, a framework that performs selective substructure encoding in molecular line graphs with chemical bonds as the fundamental representation units, complemented by an edge-fusion graph transformer and refined SMILES-derived Morgan-fingerprint similarity profiles; on DrugBank and Twosides under transductive and inductive settings it outperforms representative baselines across multiple metrics, with ablation and visualization analyses supporting the effectiveness of selective encoding and highlighting DDI-relevant molecular substructures.
This work proposes SSE-DDI, a framework that performs selective substructure encoding in molecular line graphs with chemical bonds as the fundamental representation units, complemented by an edge-fusion graph transformer and refined SMILES-derived Morgan-fingerprint similarity profiles; on DrugBank and Twosides under transductive and inductive settings it outperforms representative baselines across multiple metrics, with ablation and visualization analyses supporting the effectiveness of selective encoding and highlighting DDI-relevant molecular substructures.