Speaker
Description
Many complex systems exhibit a modular structure: genomes are composed of genes, books consist of words, and technological systems like LEGO sets can be broken down into elementary building blocks. Representing these as component systems—collections of discrete elements—reveals a range of quantitative regularities, often shared across domains. Among these, Zipf’s law is perhaps the most well-known. In this talk, I will explore the statistical patterns that emerge in such systems and discuss possible common generative mechanisms underlying these regularities, as well as the relationships between different statistical laws. I will review several examples across domains and show how simple null models can help distinguish between universal features and system-specific behaviors. As a case study, I will focus on the cell transcriptome, treating it as a component system, and demonstrate how large-scale statistical analysis can yield biologically meaningful insights.
