NHGNN-DTA: a node-adaptive hybrid graph neural network for interpretable drug–target binding affinity prediction
Summary
NHGNN-DTA: a node-adaptive hybrid graph neural network for interpretable drug–target binding affinity prediction is a scholarly article[1].
Key Facts
NHGNN-DTA: a node-adaptive hybrid graph neural network for interpretable drug–target binding affinity prediction's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). NHGNN-DTA: a node-adaptive hybrid graph neural network for interpretable drug–target binding affinity prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/nhgnn-dta-a-node-adaptive-hybrid-graph-neural-network-for-interpretable-drugtarget-binding-affinity-prediction