The introduction of AlphaFold 2 1 has spurred a revolution in modelling the structure of
proteins and their interactions, enabling a huge range of applications in protein modelling and …

This paper presents our participation in the AGAC Track from the 2019 BioNLP Open Shared
Tasks. We provide a solution for Task 3, which aims to extract "gene - function change - …

Computational design of protein-binding proteins is a fundamental capability with broad
utility in biomedical research and biotechnology. Recent methods have made strides against …

Knowledge base construction is crucial for summarising, understanding and inferring
relationships between biomedical entities. However, for many practical applications such as drug …

The underlying structure of natural language is hierarchical; words combine into phrases,
which in turn form clauses. An awareness of this hierarchical structure can aid machine …

We study slow-roll inflation on a three-brane in a five-dimensional bulk where the effects of
energy loss from the brane due to graviton emission is included in a self-consistent manner. …

This thesis considers various extensions to the fluid/gravity correspondence as well as
problems fundamental to the study of fluid dynamics. The fluid/gravity correspondence is a map …

The problem of variable selection has received a huge amount of attention over the last 15
years, motivated by the desire to understand structure in massive datasets that are now …

Recent advancements in deep learning-based modeling of molecules promise to accelerate
in silico drug discovery. A plethora of generative models is available, building molecules …

This is the author's PhD Thesis (University of Cambridge, 2014) in its original form. In the
first part, using an invariance result, we compute the symplectic homology of contact-type …