A synthetic bidirectional expression module was constructed by placing a computationally designed minimal promoter sequence on the 5′ and 3′ sides of a transcription activation module.
Although computationally efficient because of the minimal number of parameters to be estimated, this model only captures separate reaction norm effects but fails to incorporate interactions.
For reconstruction of the measured data, several options are available ranging from very fast, approximate methods like rebinning [23 25], methods based on a limited number of histoprojections [26], or histoimages and computationally intensive listmode reconstruction methods with minimal approximations [27].
The modeler's problem is to come up with models of transportation that capture the contacts and movement important to disease spread, yet are simple enough to be computationally efficient and fit to (often minimal) data.
Instead of a minimal gene set, we computationally explored a minimal cellular-function set.
Given an engineering objective, it is theoretically possible, although computationally impractical, to find the best minimal intervention strategies.
For this model we only performed the (computationally more efficient) search for a minimal RMSD with a genetic algorithm, identifying the most temperature invariant temperature parameter set.
In this way, the number of regressions performed in the computationally intensive GLM framework is minimized, substantially reducing computation time, but at only minimal cost in terms of reduced power.
It may be used to uncover minimal hitting sets in more computationally demanding problems, where exhaustive test is unfeasible.
The complexity of addressing such a topic computationally for pathways more complex than a minimal TCS is daunting though, and must be left for the future.
