Matthew I. J. Raybould

This paper introduces FlashABB, a model that predicts antibody structures faster than sequence embedding models, enabling efficient access to 3D information for antibody stability and developability prediction.

This paper introduces Pox-AbDab, a database of antibodies against orthopoxviruses, highlighting challenges in cross-species antibody function and identifying gaps in research.

STCRpy provides a Python package for TCR structure analysis and machine learning dataset preparation, enabling tasks like complex orientation scoring and interaction profiling.

The paper evaluates TCR structure prediction models using a large dataset, finds comparable structural diversity in alpha and beta chains, and provides over 1.5M predicted structures for further analysis.

The paper introduces the OTS database, a curated resource of paired-chain TCR sequences, and develops a language model for analyzing TCR pairings and coherence.

The paper updates a tool to assess developability risks of kappa and lambda antibodies using machine learning, finding lambda antibodies have higher risk but some are more tractable.

PLAbDab is a database of over 150,000 antibody sequences and structures with literature annotations, enabling searches by sequence, structure, or keyword for functional insights.

SPACE2 improves epitope clustering by using structural models, showing higher coverage and diversity in antibodies binding the same epitope compared to sequence-based methods.

The paper compares therapeutic antibodies to NGS-derived antibody sequences to identify sequence matches and convergence between natural and artificial antibody development.