A complex adaptive system depends on numerous cause-and-effect relationships at every scale. The patterns inherent in complex adaptive systems require special modes of description. For example, the flocking patterns of birds are observed at the 'many bird' level but are the result of the forces and uncertainties that shape the behaviors of individual birds - which are in-turn shaped by numerous constraints imposed by the environment. Complex adaptive systems cannot be accurately described using 'reductionism', and instead require specialized methods that integrate multi-scale information. Advancing our understanding of biological systems in the 21st century requires theories, methods, and experiments that do just that - integrate information from the molecular to the organismal scale and beyond.
Links to a few of our favorite papers about biology and complexity.
Robert Rosen's classic essay on the distinction between mechanism and complex system in the context of the organism.
Alvaro Moreno and colleagues discuss biological regulation as stereotyped interaction between coupled dynamical systems.
Codling, Plank, and Benhamou on the analytical properties of random walks and their applications to biology.
E.M. Purcell on the forces that shape movement at the microscopic scale.
Links to Python language programming materials. They are hosted on our lab GitHub page.
Link: PyoChem I
Learn fundamentals of scientific computing for biochemistry using Python in Jupyter Notebooks.