New tool allows computer scientists to support life scientists

Assistant Professor Tin Nguyen and his lab have developed software to help life scientists efficiently analyze single-cell data using machine learning.

Tin Nguyen and his Ph.D. students Duc Tran, Hung Nguyen and Bang Tran have used the data processing power of machine learning to develop a novel tool to support the research of life scientists. Named scDHA (single-cell Decomposition using Hierarchical Autoencoder), the tool uses machine learning to address a key problem life scientists run into during their research: too much data to process. With the results of their efforts to solve this problem recently published in Nature Communications, “Fast and precise single-cell data analysis using a hierarchical autoencoder”, Nguyen’s team is now looking to serve fellow researchers by using the tool to support their analysis of large quantities of cell data.

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Tin Nguyen
Assistant Professor