Skip to content’s Molecule Property Predictor ‘Netrin’ optimised with Intel DL libraries

Netrin uses graph convolutional neural networks (GCNN) to predict properties of molecules and in doing so can be applied to drug discovery, potentially speeding up molecule screening and reducing wet lab costs. Training a GCNN for this purpose is a CPU- and memory-intensive process, and this solution brief from Intel describes the accelerated training that is possible with Intel Technologies.

The solution brief can be found here.


How can we help?

Reach out – we’d love to hear about how we can help.

We use cookies and similar technologies to enable services and functionality on our site and to understand your interaction with our service. By clicking on accept, you agree to our use of such technologies for analytics. See Privacy Policy

Leave this field blank