It’s tempting just to replicate all databases in the cloud, but it’s a much better approach to get your data house in order as part of the move. Last week I discussed database normalization as a best ...

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.

Because data is stored in tools in different formats, cross-tool metrics require data normalization to make sense of it all. Moreover, unique (and unpublished) database schemas per tool require ...

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 ...

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 ...

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, ...

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 ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Natalya Yashina is a CPA, DASM with over 12 years of experience in ...

No business can be data-driven if the only people interested in data analysis are the analysts. Just as the guidance of accountants and attorneys shapes everyday business, analytics must be integrated ...

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 ...