Paper
Personal repertoires from public T cell receptors
Or Malca, Alona Zilberberg and Sol Efroni review how machine learning reads a personal repertoire through the public T cell receptors it shares with others, in Immunological Reviews. Read more
Faculty of Life Sciences, Bar-Ilan University
Can we decode what the immune system is coding?
We study two sources of biological data: T cells and tumor cells. We produce high-throughput repertoire and transcriptome data, and we build machine-learning and network methods to read them, with the aim of helping human health.
Research
three questions we keep returning toThe T cell repertoire
Each T cell carries a receptor built by V(D)J recombination. We profile CDR3 sequences across thousands to millions of cells and build tools to read them, from cancer detection in blood to immunotherapy response.
Read moreGenomic networks
We combine pathway and network knowledge with gene and protein data to expose hidden properties of cell regulation, then test what we find at the bench.
Read moreSingle-cell transcriptomics
Droplet microfluidics captures whole transcriptomes of single cells. We use it to study epithelial cells and T cells in the tumor microenvironment.
Read moreNews
Award
We won the AIRR-ML 2025 challenge
The challenge asked teams to predict disease state from immune repertoires across eight synthetic and real datasets. Our solution matched a model to each dataset. The code is public. Read more
Paper
Breast cancer, detected from blood repertoires
Machine learning over T cell receptor repertoires from peripheral blood detects breast cancer, in npj Systems Biology and Applications. Read more