Genome editing has advanced at a rapid pace with promising results for treating genetic conditions — but there is always room for improvement. A new paper by investigators from Mass General Brigham published in Nature showcases the power of scalable protein engineering combined with machine learning to boost progress in the field of gene and cell therapy. In their study, authors developed a machine learning algorithm — known as PAMmla — that can predict the properties of about 64 million…
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News Source: www.sciencedaily.com
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