Aurélien Pélissier

IMMREP25 evaluates TCR:pMHC binding prediction for unseen peptides, showing improved performance with structural modeling but still below random guessing.

This study evaluates whether domain-specific protein language models outperform general models in immunology tasks, finding nuanced performance differences and highlighting key hyperparameters.

The paper identifies co-regulated transcription factors and BACH1 as a key driver in RA FLS using gene network analyses and experimental validation.

The paper identifies cell-specific gene regulators and networks in RA synovial tissues using RNA-seq data and computational methods, revealing key transcription factors and pathways involved in disease.

This study compares clone identification methods for B-cell repertoires and finds Shannon entropy to be the most robust diversity index, with alignment-free methods preferred for shorter reads.