Related Experiment Video
Updated: May 22, 2026
08:48
Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain
Published on: October 25, 2016
ANARCII enables alignment-free antigen receptor numbering using a generalised language model
Alexander Greenshields-Watson1, Parth Agarwal1, Sarah A Robinson1
1Department of Statistics, Oxford Protein Informatics Group, University of Oxford, Oxford, UK.
Communications Biology
|May 20, 2026
Summary
A new method called ANARCII provides accurate antigen receptor numbering without alignment. This Seq2Seq language model approach improves consistency and handles diverse antibody and T cell receptor sequences effectively.
Area of Science:
- Immunoinformatics
- Computational Biology
- Structural Biology
Background:
- Antigen receptor numbering is crucial for identifying antibody and T cell receptor binding sites.
- Current methods rely on sequence alignment, which can be inconsistent or fail for rare species/formats.
Purpose of the Study:
- To introduce ANARCII, a novel alignment-free method for antigen receptor numbering.
- To improve the accuracy, consistency, and robustness of antigen receptor sequence analysis.
Main Methods:
- Development of ANARCII, a Seq2Seq language model-based tool.
- Elimination of the need for sequence alignment to reference sets.
- Implementation of a lightweight architecture for high-throughput processing.
Main Results:
- ANARCII achieves more consistent numbering of key receptor regions.
- The method demonstrates robustness to sequence truncations and generalizes to unseen species.
- High processing speed: 90,000 sequences per minute on a high-end GPU.
Conclusions:
- ANARCII offers a superior alternative to alignment-based numbering methods.
- Enables numbering of a wider range of antibody-like sequences and facilitates comparative analysis.
- Provides better recovery of full-length regions from existing databases.
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