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Columbia University scientists have developed an AI model named General Expression Transformer (GET) to predict gene activity within cells. This innovative tool has the potential to enhance understanding of cancer and genetic diseases, and may lead to targeted gene therapies. By analyzing data from over 1.3 million cells, GET can accurately predict gene behavior even when trained on different cell types.
The model's ability to generalize predictions across various cell types represents a significant advancement in biological research. It aims to decode the complex regulatory grammar of genes, which is crucial for developing precise gene therapies. This breakthrough could revolutionize how scientists approach genetic diseases, making it easier to identify relevant genetic mutations and design effective treatments.
• GET model predicts gene activity, enhancing understanding of genetic diseases.
• AI's role in biology is transforming predictive capabilities in gene regulation.
GET is an AI model designed to predict gene activity based on learned gene regulation patterns.
Gene expression refers to the process by which genes are activated to produce proteins, influencing cell behavior.
Gene therapy involves correcting genetic mutations to treat diseases, which GET aims to facilitate through precise predictions.
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