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Information theoretic approaches analyze the statistical dependencies of interacting components by measuring the mutual information coefficients of interactions.
Biological systems can be modeled as networks of interacting components across multiple scales.
The physical world is thus seen as a net of interacting components, where there is no meaning to the state of an isolated system.
The ethylene receptors are present at very low abundance, rendering purification to homogeneity impractical for functional characterization and for the identification of interacting components.
Interacting components involve elementary signaling pathways that propagate extracellular signals to the transcriptional response level and pharmacokinetic models of corticosteroids, as putative controllers of the inflammatory response.
The native expression level of the ethylene receptors is very low, which has to date rendered purification to homogeneity from plants impractical for the identification of interacting components.
The mathematical model depicts interacting components but not processes or mechanisms by which they interact.
Cancer microcrystals in this campaign leave the ensembles of interacting components.
Many real-life systems can be modeled as complex networks, or graphs, of interacting components.
Petri net (PN) theory provides a general representation of interacting components in a network (Breitling et al., 2008).
In the case of competition pull-down assays with Cdc42, Rac and Filamin, interacting components were added simultaneously.
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