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The fruit fly Drosophila melanogaster is a model organism attractive at least in part because of its short generational time span, allowing many generations in the course of an experiment.Īt the most basic level, any abstraction of some biological phenomenon counts as a model. 1 A model organism is a species selected for genetic experimental analysis on the basis of experimental convenience, homology to other species (especially to humans), relative simplicity, or other attractive attributes. For example, biologists are quite familiar with the notion of model organisms. This challenge is compounded by our current inability to understand relationships between the components as they occur in reality, that is, in the presence of multiple, competing influences and in the broader context of time and space.ĭifferent fields of science have traditionally used models for different purposes thus, the nature of the models, the criteria for selecting good or appropriate models, and the nature of the abbreviation or simplification have varied dramatically. Human comprehension of biological systems is limited, among other things, by that very complexity and by the problems that arise when attempting to dissect a given system into simpler, more easily understood components. In biological phenomena, what is interesting and significant is usually a set of relationships-from the interaction of two molecules to the behavior of a population in its environment. Most importantly, a model is a representation of some reality that embodies some essential and interesting aspects of that reality, but not all of it.īecause all models are by definition incomplete, the central intellectual issue is whether the essential aspects of the system or phenomenon are well represented (the term “essential” has multiple meanings depending on what aspects of the phenomenon are of interest). Models can serve as explanatory or pedagogical tools, represent more explicitly the state of knowledge, predict results, or act as the objects of further experiments. Models are used because in some way, they are more accessible, convenient, or familiar to practitioners than the subject of study. In all sciences, models are used to represent, usually in an abbreviated form, a more complex and detailed reality. Indeed, such discoveries can be regarded as hypotheses asserting that the pattern or correlation may be important-a mode of “discovery science” that complements the traditional mode of science in which a hypothesis is generated by human beings and then tested empirically.įor exploring this data-rich environment, simulations and computer-driven models of biological systems are proving to be essential. In this data-rich environment, the discovery of large-scale patterns and correlations is potentially of enormous significance. And as the sizes of the datasets continue to increase exponentially, even existing techniques such as statistical analysis begin to suffer. The quantities and scopes of data being collected are now far beyond the capability of any human, or team of humans, to analyze. While the previous chapter deals with the ways in which computers and algorithms could support existing practices of biological research, this chapter introduces a different type of opportunity. Computational Modeling and Simulation as Enablers for Biological Discovery