Christin Lund‐Andersen

This study creates a single-cell immune repertoire atlas in IBD patients, revealing coordinated immune states and identifying potential therapeutic targets.

This paper introduces immuneML, a framework for unsupervised machine learning in adaptive immune receptor repertoires, demonstrating its use in generative modeling, clustering, and dataset analysis.

immuneML provides an open-source ecosystem for reproducible and interoperable machine learning analysis of adaptive immune receptor repertoires, demonstrating its utility through benchmarking and novel methods.