Instead, most tools developed for scRNA-seq rely on normalized expression measures obtained from methods developed for bulk RNA-seq or even microarray data analysis. However, whether these ...

Typically, the first transformation applied to expression data, referred to as normalization, adjusts the individual hybridization intensities to balance them appropriately so that meaningful ...

Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural ...

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 ...

Comparison of expression data requires normalization. The optimum normalization method depends on sample type, with the most common being to normalize to reference genes. It is critical to select ...

It’s a snowballing problem and one that can’t be addressed by more data collection per se, but instead finding the means to better consolidate, collate and normalize existing data into a unified ...

It’s time for traders to start paying attention to a data revolution underway that is increasingly impacting their ability to both scale their business and provide value to their clients. Capital ...

Before starting, however, pull out a piece of paper and jot down how you'd solve it. Normalizing Filenames for the Web My strategy is going to be easy: pull the string apart into individual characters ...