Abstract
AbstractThe growth and division of eukaryotic cells are regulated by complex, multi-scale networks. In this process, the mechanism of controlling cell-cycle progression has to be robust against inherent noise in the system. In this paper, a hybrid stochastic model is developed to study the effects of noise on the control mechanism of the budding yeast cell cycle. The modeling approach leverages, in a single multi-scale model, the advantages of two regimes: (1) the computational efficiency of a deterministic approach, and (2) the accuracy of stochastic simulations. Our results show that this hybrid stochastic model achieves high computational efficiency while generating simulation results that match very well with published experimental measurements.
Funder
NSF | Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations
NSF | BIO | Division of Molecular and Cellular Biosciences
U.S. Department of Health & Human Services | NIH | Center for Information Technology
National Science Foundation
U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications,Drug Discovery,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation
Cited by
8 articles.
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