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ML for immune repertoire profiling and cancer immunotherapy. Antigen recognition prediction via structural modelling.

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ISALGO

From immune sequences
to antigen recognition.

Immunosequencing Algorithms Laboratory

Algorithms, curated data and structural models for adaptive immunity.

Laboratory   /   Software   /   Datasets   /   VDJdb

We study how immune receptors recognise antigens. Our work connects repertoire sequencing, antigen-specificity annotation and TCR–peptide–MHC structure, with applications in infection, vaccination and cancer immunotherapy.

Sequence. Structure. Specificity.

Read the repertoire. Map receptor genes, resolve sequencing errors and analyse T- and B-cell receptor diversity.

Connect receptors to targets. Curate experimentally characterised T-cell receptors and develop methods for specificity annotation.

Model recognition. Study receptor–peptide–MHC interactions and peptide immunogenicity to inform neoantigen research.

An open research toolkit

Resource Research use
VDJdb Curated T-cell receptors with known antigen specificity
VDJmatch Match repertoires against antigen-specificity references
TCRen Structure-based modelling of TCR–pMHC recognition
MHCmatch MHC binding prediction and peptide mimic search
VDJtools Immune-repertoire analysis
mir.py Machine learning for immune repertoires
arda Receptor gene mapping and domain annotation
MIGEC Molecular-identifier-based sequencing workflows

Data for discovery

Explore our Hugging Face datasets for repertoire analysis and structural immunology. Each repository provides its own scope, provenance and terms of use; follow its dataset card when selecting inputs for research.

Research & collaboration

Led by Dr. Shugay, ISALGO develops computational methods at the interface of immunology and data science. Find the team, research directions and selected publications on isalgo.dev.

For software questions and contributions, use the relevant AntigenOmics repository. For research enquiries, contact the laboratory.

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