This interactive animation shows how the structure of the global import trade network changed from 1993 through 2025. Countries are grouped into subnetworks using the Leiden community-detection algorithm applied to directed, weighted bilateral import data from the IMF. Each color represents a detected trade subnet for a given year, and the timeline allows viewers to follow changes in countries’ subnet memberships over time. Subnet numbers are algorithmic labels and should not be interpreted as fixed groups across all years.

`R` is a programming language and free software environment for statistical computing and graphics. It's not only a powerful statistical programming language but also the go-to data analysis tool for many computational genomics experts. We will explore how high-dimensional genomics datasets can be analyzed with core R packages and functions.

Large biological datasets are often too big to understand by reading numbers in a table. In DREAM-High, we will eventually use heatmaps to look for patterns in breast cancer gene expression data from patients in The Cancer Genome Atlas. A heatmap can help us ask questions such as: - Which samples look similar to each other? - Which genes behave similarly across patients? - Can visual patterns help us discover tumor subtypes? Today we will learn the same basic idea using a small practice dataset that comes with R.