ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction
Summary
ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction is a scholarly article[1].
Key Facts
ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/scannet-an-interpretable-geometric-deep-learning-model-for-structure-based-protein-binding-site-prediction
MLA“ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/scannet-an-interpretable-geometric-deep-learning-model-for-structure-based-protein-binding-site-prediction.
BibTeX@misc{4ortxyz_scannet-an-interpretable-geometric-deep-learning-model-for-structure-based-protein-binding-site-prediction_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction}}, year = {2026}, url = {https://4ort.xyz/entity/scannet-an-interpretable-geometric-deep-learning-model-for-structure-based-protein-binding-site-prediction}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction — https://4ort.xyz/entity/scannet-an-interpretable-geometric-deep-learning-model-for-structure-based-protein-binding-site-prediction (retrieved 2026-05-24)
