title: State observer design for delayed genetic regulatory networks.
abstract: Genetic regulatory networks are dynamic systems which describe the interactions among gene products (mRNAs and proteins). The internal states of a genetic regulatory network consist of the concentrations of mRNA and proteins involved in it, which are very helpful in understanding its dynamic behaviors. However, because of some limitations such as experiment techniques, not all internal states of genetic regulatory network can be effectively measured. Therefore it becomes an important issue to estimate the unmeasured states via the available measurements. In this study, we design a state observer to estimate the states of genetic regulatory networks with time delays from available measurements. Furthermore, based on linear matrix inequality (LMI) approach, a criterion is established to guarantee that the dynamic of estimation error is globally asymptotically stable. A gene repressillatory network is employed to illustrate the effectiveness of our design approach.
authors: School of Information, Beijing Wuzi University, Beijing 101149, China.
authors: Li-Ping
authors: LP
authors: Tian
authors: College of Mathematics and Statistics, Hebei University of Economics and Business, Shijiazhuang, Hebei 050061, China.
authors: Zhi-Jun
authors: ZJ
authors: Wang
authors: Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9.
authors: Amin
authors: 0000-0003-3282-2773
authors: A
authors: Mohammadbagheri
authors: Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9 ; Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9.
authors: Fang-Xiang
authors: 0000-0002-4593-9332
authors: FX
authors: Wu
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D053263:Gene Regulatory Networks; D006801:Humans; D016014:Linear Models; D008957:Models, Genetic; D011506:Proteins / Q000378:metabolism; D012333:RNA, Messenger / Q000378:metabolism; D015203:Reproducibility of Results; D012984:Software; D013997:Time Factors
chemical_list: D011506:Proteins; D012333:RNA, Messenger