The normalization of RNA-seq data is essential for accurate downstream inference, but the assumptions upon which most normalization methods are based are not applicable in the single-cell setting.

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

We collected a unique pair of microRNA sequencing data sets for the same set of tumor samples; one data set was collected with and the other without uniform handling and balanced design. The former ...

A good way to understand data normalization and see where this article is headed is to take a look at the screenshot of a demo program in Figure 1. The demo uses a small text file named ...

Understanding and correcting variability in western blot experiments is essential for reliable quantitative results. Experimental errors from pipetting, gel transfer, or sample differences can distort ...