Stochastic cell cycle modeling for budding yeast

Authors:
Tae-Hyuk Ahn;Pengyuan Wang;Layne T. Watson;Yang Cao;Clifford A. Shaffer;William T. Baumann
Affiliations:
Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Cisco Systems, Inc.;Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Virginia Polytechnic Institute and State University, Blacksburg, Virginia
Venue:
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Year:
2009

Citing 1
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Parallel stochastic simulations of budding yeast cell cycle: load balancing strategies and theoretical analysis

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Abstract

The budding yeast cell cycle provides an excellent example of the need for modeling stochastic effects in mathematical modeling of biochemical reactions. The continuous deterministic approach using ordinary differential equations is adequate for understanding the average behavior of cells, while the discrete stochastic approach accurately captures noisy events in the growth-division cycle. This paper presents a stochastic approximation of the cell cycle for budding yeast using Gillespie's stochastic simulation algorithm. To compare the stochastic results with the average behavior, the simulation must be run thousands of times. A load balancing algorithm reduces the cost for making those runs by 14% when run on a parallel supercomputer.