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The robust molecular noise attenuation problem will be systematically discussed for gene networks with multiple process delays from the nonlinear H∞ stochastic signal-processing perspective.
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In this study, the robust nonlinear stochastic H∞ filtering theory is applied to discuss the robust stability and noise filtering problems of nonlinear stochastic gene networks under both multiple-time delays due to biochemical process delays and stochastic intrinsic molecular noise due to parameter fluctuations.
A nonlinear stochastic dynamic model with multiple time delays is proposed for describing a gene network under process delays, intrinsic molecular fluctuations, and extrinsic molecular noises.
In this study, the random parameter fluctuations are modeled as state-dependent intrinsic molecular fluctuations of the stochastic gene network model in which multiple-time delays of biochemical process is also considered to mimic the process delays in gene regulation processes.
As each of these molecular events is subject to significant biochemical process delays, intrinsic fluctuations, and extrinsic disturbances, gene expression is best viewed as a nonlinear stochastic process with multiple time delays [ 1- 4].
Two-step testing, promoted by the NIH panel to limit false positives, clearly delays GDM diagnosis, misses 25% of GDM cases even with optimal follow-up, and gives the opportunity for multiple process errors.
Some process activity and flow models are for multiple processes.
That process delayed approval of Raptiva by nearly two years.
Multiple processes are monitored.
In this paper, a pre-compensator is designed in order to convert a multiple time-delays process to one with a single time-delay in the forward path.
The complexity is reflected by the existence of strong process coupling, multiple time delays, and large time variations.
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