Prerequisites for effective experimentation in computational biology

The development of any given biological model is driven by the experimental context in which it will be used. Hence, computer models are often overfitted to a single, unique, experimental context and fail to be useful in other situations. So doing severely limits the model's usefulness, effectively blocking inferential extensions to somewhat different conditions. To solve this problem, multiple, separate models of a biological system are required to adequately represent that system's behaviors. This is in stark contrast to the biological components to which these models refer. They function in many different situations, which is often not the case for mechanical components. The problem presents a fundamental breakdown in the extent to which any computer model represents its biological referent, especially when considering these functional units in a complex, medically relevant context. In this paper, we present the basics of a modeling method, FURM (Functional Unit Representation Method) that attempts to address this breakdown by enforcing and encouraging the use of some basic methodological principles in the development of any functional unit model.