Case Study: Cancer Research UK models tumor growth faster and more openly with Julia Computing

UK cancer researchers use Julia to model tumor growth, informing interpretation of cancer genomes

Cancer Research UK needed a fast, readable way to simulate tumor growth and interpret cancer genomes, especially for Approximate Bayesian Computation workflows that can require millions of simulations. They turned to Julia Computing and the Julia language to build evolutionary models of cancer development in a more open, reproducible way.

With Julia Computing’s Julia platform, the researchers implemented both the tumor-growth model and the inference framework in a single language, avoiding the need to switch between tools. The result was significantly faster evolutionary simulations compared with other languages, while also making the code cleaner, easier to understand, and better suited for reproducible scientific research.

Cancer Research UK