This is the 3rd part of the 3 part series. Read part 1 and part 2 here. Part 3: Why industrializing interpretation is now more […]
This is the 2nd part of the 3 part series. Read part 1 here. Part 2: Data interpretation requires context and awareness about available algorithms […]
This is the 1st part in a 3 part series. Part 1: The bottleneck is not data generation In 1951 Frederick Sanger first found out […]
Data scientists are aware of the iterative nature of their fields. Writing code, extensive experimentation with data, and applying different techniques to the same data […]
Probably p-value and hypothesis testing are some of the concepts that everyone has some difficulty understanding at first, considering how schools and statistics classes usually […]
With the advances in next-generation sequencing technologies over the past decade, genomics has gradually caught up to the big data giants – YouTube, Amazon, and […]
Problem Statement Principal component analysis (PCA) is a fairly common statistical technique used to reduce the dimensions of data containing a large set of interrelated variables. […]
by Sini Nagpal Many labs continue to develop experimental and computational methods to characterize the flow through metabolic enzyme(s) in cellular context [Weitzel et al].