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DPre is a bioinformatic tool that enables the user to explore cell type conversion/ differentiation experiments. DPre may take the expression or the differentially regulated genes of the samples to rate transcriptional similarity with a reference dataset, the targets.
This project is a comparative study of Autoencoder (AE) and Principal Component Analysis (PCA) for dimensionality reduction in gene expression data. It aims to understand the unique capabilities and applications of both methods in handling high-dimensional biological data.