Advances in gene sequencing technology and computing power have significantly increased the availability of bioinformatic data and processing capabilities. This convergence provides an ideal opportunity for artificial intelligence (AI) to develop methods to control cellular behavior.
In a new study, Northwestern University researchers have reaped fruit from this nexus by developing an AI-powered transfer learning approach that repurposes publicly available data to predict combinations of gene perturbations that can transform cell type or restore diseased cells to health.
The study was recently published in the Proceedings of the National Academy of Sciences.
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