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In line with the CA approach taken to analyse the organization of the interactions, the transcription conventions adopted represent the EK as one of the participants in the interaction.
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Searching of the interaction pairs and organization of the interaction processes are important steps in molecular dynamics (MD) algorithms and are critical to the overall efficiency of the simulation.
With a micro-analytical focus on the architecture of turns, turn taking and the sequential organization of the interaction, the analysis shows how intersubjectivity is reached interactionally by the participants.
The emergent behaviors of nature are not only the sum of interactions among ecosystem parts but also depend on the organization of these interactions.
Thus, the modular organization of the genetic interactions faithfully captures a large portion of these maps.
An interesting finding of this analysis is the hierarchical organization of the regulatory interactions in the network topology.
This agrees with the idea that combinatorial organization of the regulatory interactions made ERα evolving its functions and that this combinatorial organization was more likely mediated by TEs.
Moreover, these data show that the organization of the regulatory interactions between env1, gna1 and gna3 is not strictly hierarchical, but rather functions via interconnected feedback cycles.
Thus, when evaluating a possible organization of the genetic interaction map there is a trade-off between the coverage of interactions and the number of modules and edges.
The organization of these interaction networks has been studied using graph-theoretical techniques [ 7- 9] to find global characteristics that can be mapped back to biological phenomena, such as evolutionary conserved interactions, pathway or module organization, and localization of essential proteins in the network, to mention a few.
By clustering proteins into distinct groups based on their neighborhood gene expression characteristics, we identify several significant trends in the dynamic organization of the protein interaction network.
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