Multi-target learning is a prediction task where each data example is associated with multiple target-variables (outputs) simultaneously. One of the challenges in this research field is related to the high dimensionality ...

Multi-target drugs have raised considerable interest in the last decade owing to their advantages in the treatment of complex diseases and health conditions linked to drug resistance issues. Prospective drug repositioning ...

In contrast to the one target-one drug model, multi-target agents seem as a promising alternative to manage complex disorders and health conditions linked to drug resistance issues. In fact, many longstanding drugs are in ...

Hybrid drugs are multi-target chimeric chemicals combining two or more drugs or pharmacophores covalently linked in a single molecule. In the field of anti-infective agents, they have been proposed as a possible solution ...

In contrast with the reductionist “one gene, one target, one drug” approach, network pharmacology proposes the use of multi-target therapies, a strategy that seems particularly suitable to treat disorders of complex etiology, ...

Multi-target agents have attracted great attention in the last 15 years, as they are expected to provide more efficacious and safer therapeutic solutions, less prone to drug resistance phenomena. They thus seem particularly ...

The pose estimation of a surgical instrument is a common problem in the new needs of medical science. Many instrument tracking methods use markers with a known geometry that allows for solving the instrument pose as detected ...