AI predicts gene modifications and treatment targets in network biology.

TL;DR Summary
Researchers have developed an artificial intelligence (AI) system called Geneformer that can predict how gene networks control the function of cells and how disruptions in those networks cause disease. The system uses transfer learning to make predictions about how things might go wrong in disease and can be used to discover possible drug targets for disease. Geneformer was able to make accurate predictions even when only shown a very small number of examples of relevant data. The researchers used Geneformer to shed light on how heart cells go awry in heart disease, but the method can tackle many other cell types and diseases too.
Topics:health#artificial-intelligence#disease#drug-targets#gene-modifications#science-and-technology#transfer-learning
- Artificial intelligence system predicts consequences of gene modifications Medical Xpress
- Transfer learning enables predictions in network biology Nature.com
- Machine-learning model makes predictions about network biology Nature.com
- AI identifies gene interactions to speed up search for treatment targets Nature.com
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