The experience of recent years has shown that a common theme emerges in the context of machine learning (ML) and artificial intelligence (AI): the more and broader data the better. To increase the precision of predictions, it is not only necessary to have more data points but also to incorporate additional layers of information to improve the performance of the models.
In this workshop, we aim to explore how to efficiently obtain new data points that open up new dimensions for generating actionable results. From transforming de novo-generated outcomes into readily accessible molecules to structure-based optimization of interactions, we will also place a strong emphasis on an often-overlooked aspect: economic feasibility in a holistic context.
In summary, achieving better and more cost-effective results — faster.
The discussion will be accompanied by published workflow implementations applying BioSolveIT technologies.
Participants can request a certificate of attendance upon successful completion of this workshop.
