Computational Biology
AI tool links genetic mutations to likely disease categories
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Researchers at the Icahn School of Medicine at Mount Sinai have developed an artificial intelligence system called V2P that not only assesses whether genetic mutations are likely to be harmful but also predicts the broad categories of disease they may cause. The approach, described in a paper in Nature Communications, is intended to accelerate genetic diagnosis and support more personalized treatment, particularly for rare and complex conditions.
Researchers at the University of Navarra in Spain have launched RNACOREX, an open-source software that uncovers hidden genetic networks in cancer tumors. The tool analyzes thousands of molecular interactions and predicts patient survival with clarity rivaling advanced AI systems. Tested on data from 13 cancer types, it provides interpretable insights to advance cancer research.