Comparing DNA language models to guide optimal AI selection for genomics

Researchers at The University of Texas MD Anderson Cancer Center have performed a comprehensive evaluation of five artificial intelligence (AI) models trained on genomic sequences, known as DNA foundation language models. These comparisons provide valuable insights into their strengths and weaknesses and offer a framework for selecting appropriate models based on specific genomic tasks.

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