Deterministic parallel global parameter estimation for a model of the budding yeast cell cycle

被引：17
|
作者：
Panning, Thomas D. [2 ]
Watson, Layne T. [1 ]
Allen, Nicholas A. [2 ]
Chen, Katherine C. [2 ]
Shaffer, Clifford A. [2 ]
Tyson, John J. [2 ]
机构：
[1] Virginia Polytech Inst & State Univ, Dept Math & Comp Sci, Blacksburg, VA 24061 USA
[2] Virginia Polytech Inst & State Univ, Dept Comp Sci & Biol Sci, Blacksburg, VA 24061 USA
来源：
JOURNAL OF GLOBAL OPTIMIZATION | 2008年 / 40卷 / 04期
关键词：
DIRECT (DIviding RECTangles) algorithm; direct search; MADS (Mesh Adaptive Direct Search) algorithm; computational biology;
D O I：
10.1007/s10898-007-9273-7
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
Two parallel deterministic direct search algorithms are combined to find improved parameters for a system of differential equations designed to simulate the cell cycle of budding yeast. Comparing the model simulation results to experimental data is difficult because most of the experimental data is qualitative rather than quantitative. An algorithm to convert simulation results to mutant phenotypes is presented. Vectors of the 143 parameters defining the differential equation model are rated by a discontinuous objective function. Parallel results on a 2200 processor supercomputer are presented for a global optimization algorithm, DIRECT, a local optimization algorithm, MADS, and a hybrid of the two.
引用
收藏
页码：719 / 738
页数：20
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