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Targeted disruption of HLA genes via CRISPR-Cas9 generates iPSCs with enhanced immune compatibility

Machine learning model prediction The trained model was applied to predict the morphology of images of RBCs obtained from 60 donors (15 teenage males, 15 teenage females, 15 senior males, 15 senior females) and separated based on their biological age (U-, O-, and Y-RBCs) at 4 different storage time points (Day 5, 14, 28 and 42 (\( \pm \) 3 days))

Genet Res Int 2014 , 698574 (2014)

Key limitations: Some compounds have direct human pharmacodynamic data

Who it's for: Patients wanting to understand genetic contributors to chronic illness, inflammation, methylation, detoxification capacity, or treatment response