AI model learns generalized ‘language’ of regulatory genomics, predicts cellular stories

AI model learns generalized ‘language’ of regulatory genomics, predicts cellular stories

A team of investigators from Dana-Farber Cancer Institute, The Broad Institute of MIT and Harvard, Google, and Columbia University have created an artificial intelligence model that can predict which genes are expressed in any type of human cell. The model, called EpiBERT, was inspired by BERT, a deep learning model designed to understand and generate human-like language. A team of investigators from Dana-Farber Cancer Institute, The Broad Institute of MIT and Harvard, Google, and Columbia University have created an artificial intelligence model that can predict which genes are expressed in any type of human cell. The model, called EpiBERT, was inspired by BERT, a deep learning model designed to understand and generate human-like language. Cell & Microbiology Molecular & Computational biology Phys.org – latest science and technology news stories

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