Alexander Greenshields‐Watson

Fast retrieval of structurally similar antibodies from large sequence databases with AbSLang

AbSLang-search efficiently retrieves structurally similar antibodies from large sequence databases using a contrastive learning model for CDR RMSD prediction.

Reverse engineering the fatally cross-reactive A3A TCR to decouple potency and specificity

The paper reverse-engineers a TCR to reduce cross-reactivity while maintaining potency by reverting specific residues.

LICHEN: Light-chain Immunoglobulin sequence generation Conditioned on the Heavy chain and Experimental Needs

LICHEN generates light-chain antibody sequences conditioned on heavy chains and experimental needs, producing valid, diverse, and functional sequences.

ANARCII: A Generalised Language Model for Antigen Receptor Numbering

ANARCII is a language model that numbers antigen receptor sequences without alignment, achieving high accuracy and efficiency for diverse sequences.

PLAbDab-nano: a database of camelid and shark nanobodies from patents and literature

PLAbDab-nano is a database of 5000 annotated VHH and VNAR nanobody sequences from camelids and sharks, providing a resource for designing libraries and finding similar sequences.

The Observed T cell receptor Space database enables paired-chain repertoire mining, coherence analysis and language modelling

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.

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms

This study evaluates deep learning's ability to predict antibody CDR loop structures, finding limited extrapolation beyond training data but recovery with minimal structural examples.