3 papers - avg viability 7.0
A Bayesian model for drug discovery that uses variable selection to improve prediction accuracy and identify clinically meaningful drug-disease associations.
An AI-driven framework for efficient sequencing of experimental assays in drug discovery, significantly reducing resource usage.
Mozi offers a governed AI agent architecture for reliable and safe drug discovery workflows, ensuring high scientific validity in computational biology applications.