We are surrounded by a natural world of massively parallel, decentralized biological ‘information processing’ systems, a world that exhibits fascinating emergent properties in many ways. In fact, our very own bodies are the result of emergent patterns, as the development of any multi-cellular organism is determined by localized interactions among an enormous number of cells, carefully orchestrated by enzymes, signalling proteins and other molecular ‘agents.’ What is particularly striking about these highly distributed developmental processes is that a centralized control agency is completely missing. This is also the case for many other biological systems, such as termites which build their nests – without an architect that draws a plan, or brain cells evolving into a complex 'mind machine' – without an explicit blueprint of a network layout. First, I will present examples of how to use evolutionary computing to breed swarm behaviours, which shows an easy way to program, or rather breed, collectively intelligent systems. By example of an agent-based model of a gene regulatory system, I will expand the notion of swarm intelligence to the simulation of processes within a bacterial cell, which makes highly complicated biological processes much more accessible to computer-based investigations. If time permits, we will also look at a highly visual model of the immune system reactions in response to a viral attack. The talk will be concluded by demonstrations of SwarmArt, an exploratory art project which utilizes swarm intelligence and evolution.