Date / Heure
Date(s) - 28/07/2020
14h00 - 15h00

Emplacement
Événement en ligne

Catégories

Combinatorial chemistry has produced a huge amount of chemical libraries and data banks which include prospective drugs. Despite all of this progress, the fundamental problem still remains: how do we take advantage of this data to identify the prospective nature of a compound as a vital drug? Traditional methodologies fail to provide a solution to this.

Knowledge graphs, however, provide the framework which can make drug discovery much more efficient, effective and approachable. This radical advancement in technology can model biological knowledge complexity as it is found at its core. With concepts such as hyper relationships, type hierarchies, automated reasoning and analytics we can finally model, represent, and query biological knowledge at an unprecedented scale.

https://www.meetup.com/fr-FR/grakn-paris/events/270179409/