MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction

MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction

Abstract Background Drug response prediction is critical in precision medicine to determine the most effective and safe treatments for individual patients. Traditional prediction methods relying on demographic and genetic data often fall short in accuracy and robustness. Recent graph-based models, w...

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Main Authors: Dhekra Saeed, Huanlai Xing, Barakat AlBadani, Li Feng, Raeed Al-Sabri, Monir Abdullah, Amir Rehman
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Bioinformatics
Subjects:
Graph neural network
Drug response prediction
Precision medicine
Bioinformatics
Online Access:https://doi.org/10.1186/s12859-024-05987-0
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https://doi.org/10.1186/s12859-024-05987-0

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