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 ...
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 ...
Parse Biosciences & Graph Therapeutics partner to build large functional immune perturbation atlas: Seattle Thursday, January 22, 2026, 11:00 Hrs [IST] Parse Biosciences, a global ...
Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already known about genes, diseases, treatments, molecular pathways and symptoms in ...
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data networks for hidden connections – from gene functions and disease mechanisms ...
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 ...
Neo4j’s graph database underpins ‘Pegasus’ - an internal tool that Servier says could end up being mission-critical to its pharma research The R&D arm of global pharmaceutical company Servier is using ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback