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This paper introduces Evo-PU, a positive-unlabeled learning framework that models survivorship bias in protein sequence data by leveraging evolutionary mutation processes. The authors demonstrate that Evo-PU outperforms standard PU methods and protein language models in predicting protein functionality for influenza, RSV, and SARS-CoV-2.