Nature Cancer - Gfeller et al. discuss the recent technological and computational advances in prediction of TCR–epitope recognition and the therapeutic applications in cancer immunotherapy.

TCR-epitope motif-based interaction predictor. Contribute to GfellerLab/TEMPO development by creating an account on GitHub.

T cell receptor (TCR) technologies, including repertoire analyses and T cell engineering, are increasingly important in the clinical management of cellular immunity in cancer, transplantation, and other immune diseases. However, sensitive and reliable methods for repertoire analyses and TCR cloning …

Coarse-graining of large single-cell RNA-seq data into metacells - GitHub - GfellerLab/SuperCell at supercell-2.0

Interactions between T-Cell Receptors (TCRs) and antigenic peptides presented on Major Histocompatibility Complex (MHC) molecules are central to the immune recognition of infected and malignant cells....

T-Cell Receptors (TCRs) show extensive sequence diversity across T cells. This diversity arises from different choices of V and J genes and from insertions and deletions at the V(D)J junction within t...

Scientific Reports - Assessing data size requirements for training generalizable sequence-based TCR specificity models via pan-allelic MHC-I point-mutation ligandome evaluation

TCR-epitope motif-based interaction predictor. Contribute to GfellerLab/TEMPO development by creating an account on GitHub.

Interpretation of cell states using reference single-cell maps - carmonalab/ProjecTILs

Phage display and machine learning join forces to identify cancer-specific TCRs.

The [BC]2 Basel Computational Biology Conference is Switzerland's main event in the domain of Computational Biology and one of the major events of its kind in Europe. The conference unites scientists ...

AbstractSummary. Spatial Transcriptomics is revolutionizing our ability to phenotypically characterize complex biological tissues and decipher cellular nic