Machine Learning Models Predict Brain Age from Gene Expression Changes
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Researchers profiled age-related transcriptome changes in the prefrontal cortex and developed machine learning models to predict chronological age
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Thousands of transcripts were differentially expressed in older compared to younger individuals
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Some transcripts showed sex-specific expression differences between males and females
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Ontology, pathway, and network analyses identified genes and processes associated with brain aging
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Machine learning algorithms like XGBoost and LightGBM produced accurate models to predict age based on expression data