SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction.

ABSTRACT: Discovering effective anti-tumor drug combinations is crucial for advancing cancer therapy. Taking full account of intricate biological interactions is highly important in accurately predicting drug synergy. However, the extremely limited prior knowledge poses great challenges in developing current computational methods. To address this, we introduce SynergyX, a multi-modality mutual attention network to improve anti-tumor drug synergy prediction. It dynamically captures cross-modal interactions, allowing for the modeling of complex biological networks and drug interactions. A convolution-augmented attention structure is adopted to integrate multi-omic data in this framework effectively. Compared with other state-of-the-art models, SynergyX demonstrates superior predictive accuracy in both

SUBMITTER: Guo Y 

PROVIDER: S-EPMC10858681 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature