The landscape of drug discovery is evolving rapidly, driven by breakthroughs in AI, high-throughput screening and precision medicine. As researchers work to develop safer, more effective therapies, ...

Explore how large language models enhance knowledge graphs in drug discovery and improve data management and reasoning.

Explore the future of knowledge graphs and their role in scientific discovery, particularly in drug discovery advancements.

A team of scientists has uncovered the mechanism of cellular uptake for large and polar drugs and devised a novel strategy to ...

Choosing between plate reader-based assays and mass spectrometry solutions is a key decision for scientists when evaluating ...

UM researchers have developed a deep learning model to predict compound protein interactions. GraphBAN is an inductive graph-based approach. The model is all about discovering new drug candidates in ...

Interested in finding a better way to develop drugs to treat amyotrophic lateral sclerosis (ALS), Northeastern researcher ...