GATESynergy is a novel deep learning framework for predicting drug synergy that combines a hierarchical gated gene-aware encoder (HiGate) with a molecular global-local aggregator (MoGLA) that uses global query summarization to efficiently fuse drug-drug-cell line representations and capture diverse synergistic interaction patterns.
Results indicate that FragSyn, through the synergistic design of fragment-level representation and cellular context awareness, provides an effective and interpretable new approach to synergistic drug combination prediction.
Li-Feng Shao, Jianqiang Sun, Hong-Zhan Ma et al.· Journal of Chemical Informat...· 0 citations
MKASynergy, an adaptive drug synergy prediction method based on a mixture-of-experts kernel mechanism, achieves competitive predictive performance and visualization analysis confirms the model’s effectiveness in feature decoupling and helps interpret latent drug synergistic mechanisms.
Cundong Lin, Jiancheng Ni, Ying Yang et al.· Network Modeling Analysis in...· 0 citations
Identifying synergistic drug combinations is crucial for cancer treatment but poses significant challenges due to combinatorial complexity and the time-consuming wet-lab validation. This study proposes SuperGATSyn, a super-node graph attention framework for drug synergy prediction. The model introduces a cell-feature s...
Jia-Yao Xu, Xiao Chen, Xing-Chen Huang et al.· International Conference on...· 0 citations
BT-Synergy is presented, a task-specific hybrid deep learning model for drug synergy prediction that integrates BiLSTM modules within Transformer blocks to capture complementary sequential and contextual patterns from SELFIES-based molecular representations and effectively predicts synergistic interactions.
Sahar Abbasi Rostami, A. Lakizadeh· Discover Artificial Intellig...· 0 citations
HSSynergy, a hierarchical substructure-aware deep learning framework for predicting anticancer drug synergy, introduces a Scale-Aware Masked Attention mechanism that enforces precise layer-wise alignment, and utilizes hierarchical grouping with mask constraints to achieves same-scale focusing while shielding against cr...
Yue-Hua Feng, Shu-Cong Zhang, Xiao-Ying Yan et al.· Journal of Cheminformatics· 0 citations
SynerHyper provides a lung cancer-specific computational framework for prioritizing candidate drug combinations for downstream experimental validation and an accessible online prediction server that integrates three-dimensional molecular representations, transcriptomic profiles, hypergraph learning, and ensemble fusion...
Chuan-Ce Sun, Ling-Hao Zhang, Xiao-Tang Huang et al.· International Journal of Mol...· 0 citations
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