TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation

Research article (Bioinformatics, 2021) · cited 59× · AI/ML
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TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation

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TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation. Retrieved May 24, 2026, from https://4ort.xyz/entity/tgsa-proteinprotein-association-based-twin-graph-neural-networks-for-drug-response-prediction-with-similarity-augmentati
MLA “TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/tgsa-proteinprotein-association-based-twin-graph-neural-networks-for-drug-response-prediction-with-similarity-augmentati.
BibTeX @misc{4ortxyz_tgsa-proteinprotein-association-based-twin-graph-neural-networks-for-drug-response-prediction-with-similarity-augmentati_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation}}, year = {2026}, url = {https://4ort.xyz/entity/tgsa-proteinprotein-association-based-twin-graph-neural-networks-for-drug-response-prediction-with-similarity-augmentati}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): TGSA: protein–protein association-based twin graph neural networks for drug response prediction with similarity augmentation — https://4ort.xyz/entity/tgsa-proteinprotein-association-based-twin-graph-neural-networks-for-drug-response-prediction-with-similarity-augmentati (retrieved 2026-05-24)

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