To Appear In: Bonchev, D. and Rouvray, D. (eds.) (2004, in press). Complexity in Chemistry, Biology and Ecology. Kluwer Academic Press, New York, N.Y. Cellular Automata Models of Complex Biochemical Systems Lemont B. Kier and Tarynn M. Witten Center for the Study of Biological Complexity Virginia Commonwealth University, Richmond, Va 23284 1. Reality, systems, and models 2. General principles of complexity 3. Modeling emergence in complex biosystems 4. Examples of cellular automata models 5. Summary 1. Reality, systems, and models 1.1 Introduction The role of a scientist is to study nature and to attempt to unlock her secrets. In order to pursue this goal, a certain process is usually followed, normally starting with observations. The scientist observes some part of the natural world and attempts to find patterns in the behaviors observed. These patterns, when they are found in what may be a quite complicated set of events, are then called the laws of behavior for the particular part of nature that has been studied. However, the process does not stop at this point. Scientists are not content merely to observe nature and catalog patterns, they seek explanations for the patterns. The possible explanations, that scientists propose, take the form of hypotheses and theories in the form of models. The models serve as representations about how things work behind the scenes of appearance. One way to describe the modeling process is to express it as a pictorial algorithm or flow diagram shown in Figure 1.