Single-cell RNA sequencing (scRNA-seq) has transformed the field of transcriptomics by making it possible for researchers to address fundamental questions that could not be tackled by bulk-level ...

(Left) Current dimensionality reduction methods for scRNA-seq data involve conventional data preprocessing steps, such as log normalization, followed by manual selection of signals from the scaled ...

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 ...

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 ...

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 ...

What is data cleaning in machine learning? Data cleaning in machine learning (ML) is an indispensable process that significantly influences the accuracy and reliability of predictive models. It ...

See a spike in your DNA–protein interaction quantification results with these guidelines for spike-in normalization. A team of researchers at the University of California San Diego (CA, USA) have ...