Differential simulated annealing: a robust and efficient global   optimization algorithm for parameter estimation of biological networks

doi:10.1039/c4mb00100a

CORC > 北京大学 > 化学与分子工程学院

	Differential simulated annealing: a robust and efficient global optimization algorithm for parameter estimation of biological networks
	Dai, Ziwei ; Lai, Luhua
刊名	分子生物系统
	2014
关键词	BIOCHEMICAL PATHWAYS STOCHASTIC RANKING KINETIC-MODELS VARIABLES EVOLUTION STRATEGY
DOI	10.1039/c4mb00100a
英文摘要	Ordinary differential equations (ODEs) are widely used to model the dynamic properties of biological networks. Due to the complexity of biological networks and limited quantitative experimental data available, estimating kinetic parameters for these models remains challenging. We present a novel global optimization algorithm, differential simulated annealing (DSA), for estimating kinetic parameters for biological network models robustly and efficiently. DSA was tested on 95 models sizing from a few to several hundreds of parameters from the BioModels database and compared with other five widely used algorithms for parameter estimation, including both deterministic and stochastic optimization algorithms. Our study showed that DSA gave the highest success rate in the whole dataset and performed especially well for large models. Further analysis revealed that DSA outperformed the five algorithms compared in both accuracy and efficiency.; Biochemistry & Molecular Biology; SCI(E); PubMed; 0; ARTICLE; lhlai@pku.edu.cn; 6; 1385-1392; 10
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/189539]
专题	化学与分子工程学院生命科学学院
推荐引用方式 GB/T 7714	Dai, Ziwei,Lai, Luhua. Differential simulated annealing: a robust and efficient global optimization algorithm for parameter estimation of biological networks[J]. 分子生物系统,2014.
APA	Dai, Ziwei,&Lai, Luhua.(2014).Differential simulated annealing: a robust and efficient global optimization algorithm for parameter estimation of biological networks.分子生物系统.
MLA	Dai, Ziwei,et al."Differential simulated annealing: a robust and efficient global optimization algorithm for parameter estimation of biological networks".分子生物系统 (2014).