Parameter estimation for metabolic networks with two stage Bregman regularization homotopy inversion algorithm.
Metabolism is a very important cellular process and its malfunction contributes to human disease. Therefore, building dynamic models for metabolic networks with experimental data in order to analyze biological process rationally has attracted a lot of attention. Owing to the technical limitations, some unknown parameters contained in models need to be estimated effectively by means of the computational method. Generally, problems of parameter estimation of nonlinear biological network are known to be ill condition and multimodal. In particular, with the increasing amount and enlarging the scope of parameters, many optimization algorithms often fail to find a global solution. In this paper, two-stage variable factor Bregman regularization homotopy method is proposed. Discrete homotopy is used to identify the possible extreme region and continuous homotopy is executed for the purpose of stability of path tracing in the special region. Meanwhile, Latin hypercube sampling is introduced to get the good initial guess value and a perturbation strategy is developed to jump out of the local optimum. Three metabolic network inverse problems are investigated to demonstrate the effectiveness of the proposed method.
School of Computer Science and Technology, Dalian University of Technology, Dalian, China; Department of Computer Science, Dalian Neusoft Institute of Technology, Dalian, China.
Hong
H
Wang
School of Computer Science and Technology, Dalian University of Technology, Dalian, China; State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China. Electronic address: forget1life@gmail.com.
Xi-cheng
XC
Wang
D000465:Algorithms; D016718:Arachidonic Acid / Q000378:metabolism; D001792:Blood Platelets / Q000378:metabolism; D042783:Endothelial Cells / Q000378:metabolism; D006801:Humans; D007963:Leukocytes, Mononuclear / Q000378:metabolism; D053858:Metabolic Networks and Pathways
D016718:Arachidonic Acid
Large scale; Ordinary differential equation; Strong nonlinear