For a full list of publications, see Google Scholar.

Highlights from recent publications

Ontologies are computable representations of knowledge in a particular domain. They are widely used in biomedicine to catalogue and capture relevant biomedical knowledge across a range of different types of entity such as diagnoses, proteins, metabolites, and types of behaviour. While it is widely acknowledged that developing ontologies requires a combination of domain expertise and technical expertise, it is less well known that ontology development also requires important social skills such as the ability to mediate! Read more about the role of ontologists in bringing about consensus in a publication forthcoming in the Applied Ontology journal — read the preprint here.

The Human Behaviour-Change Project is creating a knowledge system for behaviour science. To support this knowledge system, we developed a novel semantics-driven machine learning architecture for making predictions of the outcomes of smoking cessation interventions and giving explanations for those predictions in the form of weighted rules. Read more about this innovative approach here, in the proceedings of the 2022 workshop on neural-symbolic learning and reasoning (NeSy).

Predicting chemical classes for a novel chemical structure is a useful task for many applications in the study of metabolism, as well as in maintaining chemical knowledge resources. We have been exploring how best to apply deep learning to this task, and how to use the internal parameters of the trained model to give visual explanations for the model’s predictions. Read more here.