A comparison of clustering models for inference of T cell receptor antigen specificity

A comparison of clustering models for inference of T cell receptor antigen specificity

Blog Article

The vast potential sequence diversity of TCRs and Prevalence and risk factors for dementia and mild cognitive impairment among older people in Southeast China: a community-based study their ligands has presented an historic barrier to computational prediction of TCR epitope specificity, a holy grail of quantitative immunology.One common approach is to cluster sequences together, on the assumption that similar receptors bind similar epitopes.Here, we provide the first independent evaluation of widely used clustering algorithms for TCR specificity inference, observing some variability in predictive performance between models, and marked differences in scalability.

Despite USE OF AUTHENTIC FILMS WITH SUBTITLES IN THE PROCESS OF LEARNING NEW VOCABULARY IN HIGHER EDUCATION SECTOR (AS BASED ON THE ENGLISH LANGUAGE MATERIAL) these differences, we find that different algorithms produce clusters with high degrees of similarity for receptors recognising the same epitope.Our analysis strengthens the case for use of clustering models to identify signals of common specificity from large repertoires, whilst highlighting scope for improvement of complex models over simple comparators.