Predicting Cell Phenotypes from scRNAseq Data

  Ryan Nayebi* Mentor: Brianna Chrisman *Woodside Priory School Abstract The use of machine learning to analyse data obtained through single-cell RNA sequencing (scRNAseq) provides eye-opening insights into cellular biology. Applications of this type of data analysis range from understanding tumor heterogeneity (with potential for creating lifesaving, patient-specific treatment) to studying stochastic gene expression.[17] Throughout …

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