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 ...

As some scientists create huge, new, single-nucleus RNA-sequencing datasets, others devise ways to better use existing ones. At the Alzheimer’s Association International Conference held last month in ...

Scientists have developed a new extraction protocol for RNA-seq and metabolomic analysis, offering a more complete picture of cellular activity than either technique on its own. The protocol ...

RNA-Seq has advanced our ability to characterize transcriptomes at high resolution, and the laboratory and data analysis techniques used for this NGS application continue to mature, notes John Tan ...

Mapping RNA sequencing data to understand gene expression can be difficult because the RNA sequences are spliced by cellular mechanisms, meaning one set of RNA data can come from non-connected ...

Methods for depth normalization have been assessed primarily with simulated data or cell-line–mixture data. There is a pressing need for benchmark data enabling a more realistic and objective ...

Avoiding the formation of unwanted clusters of similar elements when dividing data into groups is of great importance for the ...

RNA-Seq data analysis to identify enriched metabolic pathways and a prognostic signature in squamous cell lung cancer.

In the past decade there has been significant interest in studying the expression of our genetic code down to the level of ...