Advancing drug–target interaction prediction: a comprehensive graph-based approach integrating knowledge graph embedding and ProtBert pretraining

Advancing drug–target interaction prediction: a comprehensive graph-based approach integrating knowledge graph embedding and ProtBert pretraining

Abstract Background The pharmaceutical field faces a significant challenge in validating drug target interactions (DTIs) due to the time and cost involved, leading to only a fraction being experimentally verified. To expedite drug discovery, accurate computational methods are essential for predictin...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Warith Eddine Djeddi, Khalil Hermi, Sadok Ben Yahia, Gayo Diallo
Aineistotyyppi: Artikkeli
Kieli:English
Julkaistu: BMC 2023-12-01
Sarja:BMC Bioinformatics
Aiheet:
Drug–target interaction prediction
Knowledge graph embedding
COVID-19
Cosine similarity
ProtBERT
Linkit:https://doi.org/10.1186/s12859-023-05593-6

Internet

https://doi.org/10.1186/s12859-023-05593-6

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