Normalization of RNA-sequencing (RNA-seq) data has proven essential to ensure accurate inference of expression levels. Here, we show that usual normalization approaches mostly account for sequencing ...

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 ...

When normalizing data structures, attributes congregate around the business keys that identify the grain at which those attributes derive their values. Attributes directly related to a person, ...

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 ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

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 ...

Whether correction of anemia in patients with stage 3 or 4 chronic kidney disease improves cardiovascular outcomes is not established. We randomly assigned 603 patients with an estimated glomerular ...

There are many types of experimental methods that often use normalization to fix the differences induced by factors other than what is immediately being analyzed. In particular, normalization can be ...

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 ...