Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification
Background Machine learning (ML) methodology development for the classification of
immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of …
immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of …
Evaluating the utility of amino acid similarity-aware kmers to represent TCR repertoires for classification
Insights gained through interpretation of models trained on the T-cell receptor (TCR)
repertoire to infer presence of immune-mediated conditions could contribute to advances in …
repertoire to infer presence of immune-mediated conditions could contribute to advances in …
Reconstituting T cell receptor selection in-silico
Each T cell receptor (TCR) gene is created without regard for which substances (antigens)
the receptor can recognize. T cell selection culls developing T cells when their TCRs (i) fail …
the receptor can recognize. T cell selection culls developing T cells when their TCRs (i) fail …