The development of any given biological model is driven by the experimental context in which it will be used. Hence, computer models are often over-fitted to a single, unique, experimental context and fail to be useful in other situations. 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, which can be placed in almost any experimental context relevant to their various behaviors. The problem presents a fundamental breakdown in the extent to which any computer model represents its referent. 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.
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2013-05-16
| New paper: Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity, published in Wiley Interdisciplinary Reviews: Systems Biology and Medicine. This one walks through various use cases extracted and derived from various more tightly focused modeling and simulation papers. It also lays out a vision for an analog based model repository, including the features such a repository requires in order to satisfy its use cases. In particular, we talk about the need for embedded knowledge inside models.
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