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Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction

Identifying and characterizing secreted virulence proteins are fundamental for deciphering microbial pathogenicity. Here, the authors introduce a practical training framework to improve protein language model representations by integrating biological features and prior information through contrastive learning.