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Protein language models learn from diverse sequences spanning the evolutionary tree and have proven to be powerful tools for sequence design, variant effect prediction and structure prediction. What are the foundations of protein language models, and how are they applied in protein engineering?
Models like ChatGPT and DALL-E2 generate text and images in response to a text prompt. Despite different data and goals, how can generative models be useful for protein engineering?
