In addition to our proprietary work, we also contribute to research articles, host seminars, and attend speaking events. Visit the connect page to enquire about engagement opportunities.
Here is some more information about Molecule.one.
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design.
We investigate the feasibility of training deep graph neural networks to approximate the outputs of a retrosynthesis planning software, and their use to bias the search result
We proposed Molecule Edit Graph Attention Network (MEGAN), a template free neural model that encodes reaction as a sequence of graph edit.