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We present a stochastic model of transcription that considers these complex regulatory mechanisms.
We present a stochastic model of the natural history of invasive breast cancer that quantifies (1) the relative rate that the disease transitions from the local, regional to distant stages, (2) the tumour volume at the stage transitions and (3) the impact of symptom-prompted detection on the tumour size and stage of invasive breast cancer in a population not screened by mammography.
We then present a stochastic model of user behavior on Digg that explicitly includes dependencies on social network links.
We present a stochastic model of codon usage, thereby allowing ORFs to be evaluated in terms of their deviation from an expected codon composition.
Below, we present a stochastic model of TF-DNA binding and dissociation together with the a method which allow us to estimate not only, but also N0.
We present a stochastic model of gene expression that accounts for the main biochemical processes that describe the QS mechanism close to its activation threshold.
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We present a stochastic model for the spread of smallpox after a small number of index cases are introduced into a susceptible population.
This paper presents a stochastic model of the multi-stage global supply chain network problem, incorporating a set of related risks, namely, supply, demand, exchange, and disruption.
This paper presents a stochastic model of exchange rates, which is used to explain the forward premium anomaly.
The article of Gubbins et al. [22] cited the largest number of references belonging to C1 group (9 citations); it presents a stochastic model of fungicide resistance evolution that quotes six models of antibiotic resistance and three general models from population biology.
We have presented a stochastic model to analyze the dynamic properties of genetic regulatory networks with parameter uncertainties, external disturbances and functional variations in the host cell.
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