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Abstract Protein language models can now predict function and mutational effects directly from sequence, yet only a few incorporate function-deciding structural information with minimal additional effort. We introduce ProBEiT, a multimodal architecture that jointly encodes amino-acid sequences and discrete, tokenized structures via a parameter-efficient implicit mixture-of-experts scheme with deterministic routing.
BRIEF COMMUNICATION Songzhe He, Tao Li, and Hao Feng contributed equally to this work. Abstract Background Xenoantigens other than Gal, Neu5Gc, and Sda may be playing a role in pig graft rejection. We investigated the incidence of antibodies to unknown pig xenoantigen in different human groups.
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