NDLI: Approximation of a multi-scale model based on multiple site phosphorylation

Content Provider	IEEE Xplore Digital Library
Author	Zhen Liu Yang Cao
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, Virginia Tech, Blacksburg, VA 24061 (Zhen Liu; Yang Cao)
Abstract	The increasing complexity of the modeling of the budding yeast cell cycle control system demands development of efficient stochastic simulation algorithms. Specifically, models with multi-scale and multi-state features present great difficulties in simulation efficiency. The coexistence of the very fast and very slow reactions in one model usually leads to great challenges to the Stochastic Simulation Algorithm (SSA) in terms of both accuracy and efficiency. The Stochastic Quasi-Steady State Assumption (SQSSA) and the hybrid simulation method, which combines the ODE solver and SSA, are two commonly used approximation methods for stochastic simulation. In this paper we consider biological models based on multiple site phosphorylation. We focus on the criterion of how to select the best method to simulate systems with multi-scale and multi-site features. We propose an efficient method to approximate the relaxation time of the subsystem that is supposed to be on the fast time scale. Then we discuss the best scenario for each method to be selected using the proposed approximated relaxation time. At last, we apply the SQSSA and the hybrid method to a bistable switch model based on multiple site phosphorylation, and compare the accuracy and efficiency of the two methods with the exact SSA via numerical experiments.
Starting Page	9
Ending Page	16
File Size	1168868
Page Count	8
File Format	PDF
ISBN	9781467327466
e-ISBN	9781467327473
e-ISBN	9781467327442
DOI	10.1109/BIBMW.2012.6470304
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Firing Biological system modeling Stochastic processes Steady-state Mathematical model Approximation methods Equations
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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