20eddibae/sceptr-ac-tcrdist-soft

OmniTCR is a component-aware autoregressive foundation model for learning relationships among peptide epitopes, major histocompatibility complex (MHC) molecules, T-cell receptor alpha chains (TRA) and T-cell receptor beta chains (TRB).

This Hugging Face repository stores the official resources for RAMER (reaction-aware multimodal enzyme function representation model).

ClustIRR analyzes repertoires of B- and T-cell receptors. It starts by identifying communities of immune receptors with similar specificities, based on the sequences of their complementarity-determining regions (CDRs). Next, it employs a Bayesian probabilistic models to quantify differential community occupancy (DCO) between repertoires, allowing the identification of expanding or contracting communities in response to e.g. infection or cancer treatment.

A frontier protein-language generative model — because proteins deserve better small talk.

A Vision Transformer (ViT) image classification model. \ Trained by Owkin on 40 million pan-cancer histology tiles from TCGA-COAD.

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein…