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.
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.