**Frozen research plan of this challenge**

[A pre-registered protoco](https://github.com/uio-bmi/adaptive_immune_profiling_challenge_2025/blob/main/registered_report.pdf)l describing all the details of the competition including extensive background information, dataset descriptions, evaluation process, and pilot data providing reference benchmarks

**What's the state-of-the-art in mining Adaptive Immune Repertoires?**

- [A summary from domain experts](https://www.sciencedirect.com/science/article/pii/S2452310020300524)

- [A perspective from domain experts](https://www.sciencedirect.com/science/article/pii/S2405471224003429)

**Examples of state-of-the-art methods**

- [Modern Hopfield Networks and Attention for Immune Repertoire Classification](https://doi.org/10.1101/2020.04.12.038158)

- [Immunosequencing of the T-Cell Receptor Repertoire Reveals Signatures Specific for Identification and Characterization of Early Lyme Disease](https://www.medrxiv.org/content/10.1101/2021.07.30.21261353v2.full)

- [Disease diagnostics using machine learning of B cell and T cell receptor sequences](https://pmc.ncbi.nlm.nih.gov/articles/PMC12061481/)

- [A platform for ML on adaptive immune repertoires with a wide collection of encodings and ML methods](https://pmc.ncbi.nlm.nih.gov/articles/PMC10312379/)