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Multi-source graph learning may improve drug–target affinity prediction

Figure 1. Overall framework of MIGDTA. GCN: graph convolutional network; GIN: graph isomorphism network; CNN: convolutional neural network; MLP: multi-layer ...
Phys.org

Graph learning modules enhance drug-target interaction predictions

The identification of drug-target Interactions (DTIs) represents a pivotal link in the process of drug development and design. It plays a crucial role in narrowing the screening range of candidate ...
EurekAlert!

DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction

Exploring the biomedical interactions about chemical compounds and protein targets is crucial for drug discovery. Determining these interactions (DDI/DTI) not only reveals the potential synergistic ...
inc42

Graph AI Raises $3 Mn To Automate Drug Safety Monitoring for Pharma Firms

Pharmaceutical-sector focussed AI startup Graph AI’s $3 Mn seed funding round was led by Bessemer Venture Partners The startup will use the capital for product innovation, team expansion, and ...