On the complete determination of biological systems.
The nascent field of systems biology ambitiously proposes to integrate information from large-scale biology projects to create computational models that are, in some sense, complete. However, the details of what would constitute a complete systems-level model of an organism are far from clear. To provide a framework for this difficult question it is useful to define a model as a set of rules that maps a set of inputs (e.g. descriptions of the cell's environment) to a set of outputs (e.g. the concentrations of all its RNAs and proteins). We show how the properties of a model affect the required experimental sampling and estimate the number of experiments needed to "complete" a particular model. Based on these estimates, we suggest that the complete determination of a biological system is a concrete, achievable goal.
Selinger
Douglas W
DW
Harvard Medical School, Department of Genetics, 200 Longwood Ave, Boston, MA 02115, USA.
Wright
Matthew A
MA
Church
George M
GM
D002468:Cell Physiological Phenomena; D020650:Combinatorial Chemistry Techniques; D003198:Computer Simulation; D004926:Escherichia coli / Q000502:physiology; D005786:Gene Expression Regulation / Q000502:physiology; D006801:Humans; D008660:Metabolism / Q000502:physiology*; D008954:Models, Biological; D009177:Mycoplasma pneumoniae / Q000502:physiology; D020543:Proteome / Q000502:physiology; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012107:Research Design; D012680:Sensitivity and Specificity; D013045:Species Specificity; D013598:Systems Theory
D020543:Proteome