Researchers from the University of Missouri and the Ohio State University say they have created a new way to analyze data from single-cell RNA-sequencing by using machine learning. The method uses the power of computers to intelligently analyze large amounts of data and help scientists draw faster conclusions and move to the next stage of the research.

Their study “scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses” appears in Nature Communications.

“Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand challenges, including the sequencing sparsity and complex differential patterns in gene expression,” write the investigators… Continue reading.