IET Systems Biology
Volume 11, Issue 1, February 2017
Volumes & issues:
Volume 11, Issue 1
February 2017
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- Author(s): Yuangen Yao ; Chengzhang Ma ; Haiyou Deng ; Quan Liu ; Wei Cao ; Rong Gui ; Tianquan Feng ; Ming Yi
- Source: IET Systems Biology, Volume 11, Issue 1, p. 1 –7
- DOI: 10.1049/iet-syb.2015.0051
- Type: Article
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Robustness is a fundamental characteristic of biological systems since all living systems need to adapt to internal or external perturbations, unpredictable environments, stochastic events and unreliable components, and so on. A long-term challenge in systems biology is to reveal the origin of robustness underlying molecular regulator network. In this study, a simple Boolean model is used to investigate the global dynamic properties and robustness of cardiac progenitor cell (CPC) induced pluripotent stem cell network that governs reprogramming and directed differentiation process. It is demonstrated that two major attractors correspond to source and target cell phenotypes, respectively, and two dominating attracting trajectories characterise the biological pathways between two major cell phenotypes. In particular, the experimentally observed transition between different cell phenotypes can be reproduced and explained theoretically. Furthermore, the robustness of major attractors and trajectories is largely maintained with respect to small perturbations to the network. Taken together, the CPC-induced pluripotent stem cell network is extremely robustly designed for their functions.
- Author(s): Gerasimos Rigatos ; Nikolaos Zervos ; Alexey Melkikh
- Source: IET Systems Biology, Volume 11, Issue 1, p. 8 –18
- DOI: 10.1049/iet-syb.2016.0012
- Type: Article
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A new control method based on differential flatness theory is developed in this study, aiming at solving the problem of regulation of haemodynamic parameters. Actually control of the cardiac output (volume of blood pumped out by heart per unit of time) and of the arterial blood pressure is achieved through the administered infusion of cardiovascular drugs such as dopamine and sodium nitroprusside. Time delays between the control inputs and the system's outputs are taken into account. Using the principle of dynamic extension, which means that by considering certain control inputs and their derivatives as additional state variables, a state-space description for the heart's function is obtained. It is proven that the dynamic model of the heart is a differentially flat one. This enables its transformation into a linear canonical and decoupled form, for which the design of a stabilising feedback controller becomes possible. The proposed feedback controller is of proven stability and assures fast and accurate tracking of the reference setpoints by the outputs of the heart's dynamic model. Moreover, by using a Kalman filter-based disturbances’ estimator, it becomes possible to estimate in real-time and compensate for the model uncertainty and external perturbation inputs that affect the heart's model.
- Author(s): Korosh Rouhollahi ; Mehran Emadi Andani ; Seyed Mahdi Karbassi ; Iman Izadi
- Source: IET Systems Biology, Volume 11, Issue 1, p. 19 –29
- DOI: 10.1049/iet-syb.2016.0014
- Type: Article
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Deep brain stimulation (DBS) is an efficient therapy to control movement disorders of Parkinson's tremor. Stimulation of one area of basal ganglia (BG) by DBS with no feedback is the prevalent opinion. Reduction of additional stimulatory signal delivered to the brain is the advantage of using feedback. This results in reduction of side effects caused by the excessive stimulation intensity. In fact, the stimulatory intensity of controllers is decreased proportional to reduction of hand tremor. The objective of this study is to design a new controller structure to decrease three indicators: (i) the hand tremor; (ii) the level of delivered stimulation in disease condition; and (iii) the ratio of the level of delivered stimulation in health condition to disease condition. For this purpose, the authors offer a new closed-loop control structure to stimulate two areas of BG simultaneously. One area (STN: subthalamic nucleus) is stimulated by an adaptive controller with feedback error learning. The other area (GPi: globus pallidus internal) is stimulated by a partial state feedback (PSF) controller. Considering the three indicators, the results show that, stimulating two areas simultaneously leads to better performance compared with stimulating one area only. It is shown that both PSF and adaptive controllers are robust regarding system parameter uncertainties. In addition, a method is proposed to update the parameters of the BG model in real time. As a result, the parameters of the controllers can be updated based on the new parameters of the BG model.
- Author(s): Xiaoqing Cheng ; Yushan Qiu ; Wenpin Hou ; Wai-Ki Ching
- Source: IET Systems Biology, Volume 11, Issue 1, p. 30 –35
- DOI: 10.1049/iet-syb.2016.0022
- Type: Article
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Boolean network (BN) is a popular mathematical model for revealing the behaviour of a genetic regulatory network. Furthermore, observability, an important network feature, plays a significant role in understanding the underlying network. Several studies have been done on analysis of observability of BNs and complex networks. However, the observability of attractor cycles, which can serve as biomarker detection, has not yet been addressed in the literature. This is an important, interesting and challenging problem that deserves a detailed study. In this study, a novel problem was first proposed on attractor observability in BNs. Identification of the minimum set of consecutive nodes can be used to discriminate different attractors. Furthermore, it can serve as a biomarker for different disease types (represented as different attractor cycles). Then a novel integer programming method was developed to identify the desired set of nodes. The proposed approach is demonstrated and verified by numerical examples. The computational results further illustrates that the proposed model is effective and efficient.
- Author(s): Ting-Yu Kuo ; Chun-Liang Lin ; Natdanai Charoenkit ; Yang-Yi Chen ; Chakkrit Preuksakarn
- Source: IET Systems Biology, Volume 11, Issue 1, p. 36 –43
- DOI: 10.1049/iet-syb.2016.0015
- Type: Article
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Increasing applications of fundamental biological gates have been successfully built during this decade. Proceeding to the current development, this study presents a genetic arithmetic and logical unit (ALU) design based on a series of genetic logic gates. The system level's architecture consists of three parts: temp register, ALU and accumulator register. Using the concept of the ALU on the digital computer, the authors present the fundamental function of the genetic ALU via full adder register and also build the bio-storage devices to store data generated from the genetic ALU. The system in this study shows the capability of computing and storage on the biocomputer.
- Author(s): Anet J.N. Anelone and Sarah K. Spurgeon
- Source: IET Systems Biology, Volume 11, Issue 1, p. 44 –53
- DOI: 10.1049/iet-syb.2016.0028
- Type: Article
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It is demonstrated that the reachability paradigm from variable structure control theory is a suitable framework to monitor and predict the progression of the human immunodeficiency virus (HIV) infection following initiation of antiretroviral therapy (ART). A manifold is selected which characterises the infection-free steady-state. A model of HIV infection together with an associated reachability analysis is used to formulate a dynamical condition for the containment of HIV infection on the manifold. This condition is tested using data from two different HIV clinical trials which contain measurements of the CD4+ T cell count and HIV load in the peripheral blood collected from HIV infected individuals for the six month period following initiation of ART. The biological rates of the model are estimated using the multi-point identification method and data points collected in the initial period of the trial. Using the parameter estimates and the numerical solutions of the model, the predictions of the reachability analysis are shown to be consistent with the clinical diagnosis at the conclusion of the trial. The methodology captures the dynamical characteristics of eventual successful, failed and marginal outcomes. The findings evidence that the reachability analysis is an appropriate tool to monitor and develop personalised antiretroviral treatment.
Dynamics and robustness of the cardiac progenitor cell induced pluripotent stem cell network during cell phenotypes transition
Flatness-based control approach to drug infusion for cardiac function regulation
Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson's disease: a simulation study
Integer programming-based method for observability of singleton attractors in Boolean networks
Toward theoretical synthesis of biocomputer
Prediction of the containment of HIV infection by antiretroviral therapy – a variable structure control approach
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