One of the most fruitful ideas in modern science is to view processes in nature as forms of "natural computation". The genetic code, for instance, bears more than a passing resemblance to a computer program and plants grow iteratively by addition of modules according to well-defined rules.
This new paradigm has led to a host of insights about living systems, especially through the use of simulation for “virtual experiments”. By redefining computation as pathways through the network of states that a system can take, it also offers ways of understanding chaos, self-organization and many other kinds of behaviour. In recent studies, for instance, we showed that many systems (including species evolution) organize themselves through a process of "dual phase evolution" in which a system flips between different computational states.
Natural computation is now an important paradigm in computing. Nature has evolved ways to solve many complex problems so computer science is borrowing from nature. Advanced computing is often indistinguishable from biology. This is evident in the names of fields of research, such as evolutionary computing, artificial neural networks, cellular automata, machine learning and swarm intelligence.