Large language models on biological data are transforming how we analyze biological data. Their ability to process vast amounts of unstructured data makes them ideal for tasks like gene sequence prediction, protein folding, and drug discovery. By training on biological datasets, LLMs can uncover hidden patterns, generate hypotheses, and even assist in personalizing medicine. Their adaptability allows integration with bioinformatics tools for more efficient analyses.
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