The rise of machine learning (ML) has created an explosion in the potential strategies which may be used to learn from data in order to make scientific predictions. For physical scientists who wish to apply ML strategies to a particular domain, this has created a bewildering scenario, where it is difficult to make an a priori assessment of what strategy to adopt within a vast space of possibilities.
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Really excited to see work by Dr. Simon Bennie featured on the cover of this month’s issue of the Journal of Chemical Education. The paper, which you can access here, outlines how Narupa, our open-source VR-enabled interactive simulation framework, was applied to develop a computational laboratory exercise enabling undergraduate students to better understand the dynamics and interactions that guide drug-protein binding.