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The research team used artificial intelligence to study the evolutionary relationships of proteins, specifically focusing on the vertebrate kallikrein gene family, and found significant correlations between protein embeddings and sequence similarities. Despite testing various dimension reduction techniques, the initial protein embeddings without any reduction provided the most accurate insights into phylogenetic relationships, marking a substantial advancement in understanding life evolution and facilitating better drug development strategies.