Bor-Sen Chen

Publications (234)314.15 Total impact

• Article: On the Increase in Network Robustness and Decrease in Network Response Ability During the Aging Process: A Systems Biology Approach via Microarray Data.

  Chien-Ta Tu, Bor-Sen Chen
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  ABSTRACT: Aging, an extremely complex and system-level process, has attracted much attention in medical research, especially since chronic diseases are quite prevalent in the aged population. These may be the result of both gene mutations that lead to intrinsic perturbations and environmental changes that may stimulate signaling in the body. Therefore, network robustness to tolerate intrinsic perturbations and network response ability to respond external stimuli of gene network during aging process may provide insight into the systematic changes of aging. We first propose novel methods to estimate network robustness and measure network response ability of gene regulatory networks by their corresponding microarray data in aging process. Then we find that an aging-related gene network is more robust to intrinsic perturbations in the elderly than the young, and therefore is less responsive to external stimuli. Finally, response abilities of individual genes, especially FOXOs, NF-kB and p53, are significantly different in the young versus the aged subjects. These observations are consistent with experimental findings in the aged population, e.g. the elevated incidence of tumorigenesis and declining resistance to oxidative stress. The proposed method can also be used for exploring and analyzing dynamical properties for other biological processes via corresponding microarray data to provide useful information on clinical strategy and drug target selection.
  IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM 03/2013; · 2.25 Impact Factor
• Article: Identification of Infection- and Defense-Related Genes via a Dynamic Host-Pathogen Interaction Network Using a Candida Albicans -Zebrafish Infection Model.

  Zong-Yu Kuo, Yung-Jen Chuang, Chun-Cheih Chao, Fu-Chen Liu, Chung-Yu Lan, Bor-Sen Chen
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  ABSTRACT: Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs.
  Journal of Innate Immunity 02/2013; · 4.21 Impact Factor
• Article: A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Tradeoff on Phenotype Robustness in Biological Networks Part II: Ecological Networks.

  Bor-Sen Chen, Ying-Po Lin
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  ABSTRACT: In ecological networks, network robustness should be large enough to confer intrinsic robustness for tolerating intrinsic parameter fluctuations, as well as environmental robustness for resisting environmental disturbances, so that the phenotype stability of ecological networks can be maintained, thus guaranteeing phenotype robustness. However, it is difficult to analyze the network robustness of ecological systems because they are complex nonlinear partial differential stochastic systems. This paper develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance sensitivity in ecological networks. We found that the phenotype robustness criterion for ecological networks is that if intrinsic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations and environmental disturbances. These results in robust ecological networks are similar to that in robust gene regulatory networks and evolutionary networks even they have different spatial-time scales.
  Evolutionary bioinformatics online 01/2013; 9:69-85. · 1.23 Impact Factor
• Article: A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology.

  Bor-Sen Chen, Ying-Po Lin
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  ABSTRACT: Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example.
  Evolutionary bioinformatics online 01/2013; 9:87-109. · 1.23 Impact Factor
• Article: A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology.

  Bor-Sen Chen, Ying-Po Lin
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  ABSTRACT: Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view.
  Evolutionary bioinformatics online 01/2013; 9:43-68. · 1.23 Impact Factor
• Article: New Measurement Methods of Network Robustness and Response Ability via Microarray Data.

  Chien-Ta Tu, Bor-Sen Chen
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  ABSTRACT: "Robustness", the network ability to maintain systematic performance in the face of intrinsic perturbations, and "response ability", the network ability to respond to external stimuli or transduce them to downstream regulators, are two important complementary system characteristics that must be considered when discussing biological system performance. However, at present, these features cannot be measured directly for all network components in an experimental procedure. Therefore, we present two novel systematic measurement methods - Network Robustness Measurement (NRM) and Response Ability Measurement (RAM) - to estimate the network robustness and response ability of a gene regulatory network (GRN) or protein-protein interaction network (PPIN) based on the dynamic network model constructed by the corresponding microarray data. We demonstrate the efficiency of NRM and RAM in analyzing GRNs and PPINs, respectively, by considering aging- and cancer-related datasets. When applied to an aging-related GRN, our results indicate that such a network is more robust to intrinsic perturbations in the elderly than in the young, and is therefore less responsive to external stimuli. When applied to a PPIN of fibroblast and HeLa cells, we observe that the network of cancer cells possesses better robustness than that of normal cells. Moreover, the response ability of the PPIN calculated from the cancer cells is lower than that from healthy cells. Accordingly, we propose that generalized NRM and RAM methods represent effective tools for exploring and analyzing different systems-level dynamical properties via microarray data. Making use of such properties can facilitate prediction and application, providing useful information on clinical strategy, drug target selection, and design specifications of synthetic biology from a systems biology perspective.
  PLoS ONE 01/2013; 8(1):e55230. · 4.09 Impact Factor
• Source

  Available from: PubMed Central

  Article: Prediction of phenotype-associated genes via a cellular network approach: a Candida albicans infection case study.

  Yu-Chao Wang, Shin-Hao Huang, Chung-Yu Lan, Bor-Sen Chen
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  ABSTRACT: Candida albicans is the most prevalent opportunistic fungal pathogen in humans causing superficial and serious systemic infections. The infection process can be divided into three stages: adhesion, invasion, and host cell damage. To enhance our understanding of these C. albicans infection stages, this study aimed to predict phenotype-associated genes involved during these three infection stages and their roles in C. albicans-host interactions. In light of the principles that proteins that lie closer to one another in a protein interaction network are more likely to have similar functions, and that genes regulated by the same transcription factors tend to have similar functions, a cellular network approach was proposed to predict the phenotype-associated genes in this study. A total of 4, 12, and 3 genes were predicted as adhesion-, invasion-, and damage-associated genes during C. albicans infection, respectively. These predicted genes highlight the facts that cell surface components are critical for cell adhesion, and that morphogenesis is crucial for cell invasion. In addition, they provide targets for further investigations into the mechanisms of the three C. albicans infection stages. These results give insights into the responses elicited in C. albicans during interaction with the host, possibly instrumental in identifying novel therapies to treat C. albicans infection.
  PLoS ONE 01/2012; 7(4):e35339. · 4.09 Impact Factor
• Source

  Available from: nthu.edu.tw

  Article: Robust H∞ observer‐based tracking control of stochastic immune systems under environmental disturbances and measurement noises

  Bor-Sen Chen, Ying-Po Lin, Yung-Jen Chuang
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  ABSTRACT: A robust H∞ observer-based tracking control of stochastic immune response is proposed for therapeutic enhancement to track a prescribed immune response under uncertain initial states, environmental disturbances and measurement noises. The statistics of initial condition, environmental and measurement noises are assumed unavailable. Further, the state variables may not all be available and may be corrupted by measurement noises. Therefore, an observer-based control design is proposed for robust H∞ observer-based tracking control of stochastic immune systems. The robust H∞ control is designed to track a prescribed immune model response in spite of environmental disturbances, uncertain initial conditions and measurement noises. Since the stochastic immune system is highly nonlinear, it is not easy to solve the robust H∞ observer-based tracking control problem directly. A fuzzy model is proposed to interpolate several linearized stochastic immune systems to approximate the nonlinear stochastic immune system via smooth fuzzy membership functions. By the fuzzy approximation method, the H ∞ observer-based tracking control problem of stochastic immune systems could be easily solved via the linear matrix inequality (LMI) technique with the help of Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency of the proposed method.Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society
  Asian Journal of Control 08/2011; 13(5):667 - 690. · 1.03 Impact Factor
• Source

  Available from: nthu.edu.tw

  Article: Robust synthetic gene network design via library-based search method.

  Chih-Hung Wu, Hsiao-Ching Lee, Bor-Sen Chen
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  ABSTRACT: Synthetic biology aims to develop the artificial gene networks with desirable behaviors using systematic method. These networks with desired behaviors could be constructed using diverse biological parts, which may limit the development to complex synthetic gene networks. Fortunately, some well-characterized promoter libraries for engineering gene networks are widely available. Thus, a synthetic gene network can be constructed by selecting adequate promoters from promoter libraries to achieve the desired behaviors. However, the present promoter libraries cannot be directly applied to engineer a synthetic gene network. In order to efficiently select adequate promoters from promoter libraries for a synthetic gene network, promoter libraries are needed to be redefined based on the dynamic gene regulation. Based on four design specifications, a library-based search method is proposed to efficiently select the most adequate promoter set from the redefined promoter libraries by a genetic algorithm (GA) to achieve optimal reference tracking design. As the number and size of promoter libraries increase, the proposed method can play an important role in the systematic design of synthetic biology. g883743@alumni.nthu.edu.tw; bschen@ee.nthu.edu.tw Supplementary data are available at Bioinformatics online.
  Bioinformatics 08/2011; 27(19):2700-6. · 5.47 Impact Factor
• Article: Multiobjective H2/H∞ synthetic gene network design based on promoter libraries.

  Chih-Hung Wu, Weihei Zhang, Bor-Sen Chen
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  ABSTRACT: Some current promoter libraries have been developed for synthetic gene networks. But an efficient method to engineer a synthetic gene network with some desired behaviors by selecting adequate promoters from these promoter libraries has not been presented. Thus developing a systematic method to efficiently employ promoter libraries to improve the engineering of synthetic gene networks with desired behaviors is appealing for synthetic biologists. In this study, a synthetic gene network with intrinsic parameter fluctuations and environmental disturbances in vivo is modeled by a nonlinear stochastic system. In order to engineer a synthetic gene network with a desired behavior despite intrinsic parameter fluctuations and environmental disturbances in vivo, a multiobjective H(2)/H(∞) reference tracking (H(2) optimal tracking and H(∞) noise filtering) design is introduced. The H(2) optimal tracking can make the tracking errors between the behaviors of a synthetic gene network and the desired behaviors as small as possible from the minimum mean square error point of view, and the H(∞) noise filtering can attenuate all possible noises, from the worst-case noise effect point of view, to achieve a desired noise filtering ability. If the multiobjective H(2)/H(∞) reference tracking design is satisfied, the synthetic gene network can robustly and optimally track the desired behaviors, simultaneously. First, based on the dynamic gene regulation, the existing promoter libraries are redefined by their promoter activities so that they can be efficiently selected in the design procedure. Then a systematic method is developed to select an adequate promoter set from the redefined promoter libraries to synthesize a gene network satisfying these two design objectives. But the multiobjective H(2)/H(∞) reference tracking design problem needs to solve a difficult Hamilton-Jacobi Inequality (HJI)-constrained optimization problem. Therefore, the fuzzy approximation method is employed to simplify the HJI-constrained optimization problem to an equivalent linear matrix inequality (LMI)-constrained optimization problem, which can be easily solved by selecting an adequate promoter set from the redefined promoter libraries using the LMI toolbox in Matlab. Based on the confirmation of in silico design examples, we can select an adequate promoter set from the redefined promoter libraries to achieve the multiobjective H(2)/H(∞) reference tracking design. The proposed method can reduce the number of trial-and-error experiments in selecting an adequate promoter set for a synthetic gene network with desired behaviors. With the rapid increase of promoter libraries, this systematic method will accelerate progress of synthetic biology design.
  Mathematical biosciences 07/2011; 233(2):111-25. · 1.30 Impact Factor
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  Available from: nthu.edu.tw

  Article: Robust synchronization analysis in nonlinear stochastic cellular networks with time-varying delays, intracellular perturbations and intercellular noise.

  Po-Wei Chen, Bor-Sen Chen
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  ABSTRACT: Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods.
  Mathematical biosciences 05/2011; 232(2):116-34. · 1.30 Impact Factor
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  Available from: InTech

  Chapter: Robust H? Tracking Control of Stochastic Innate Immune System Under Noises

  Bor-Sen Chen, Chia-Hung Chang, Yung-Jen Chuang
  04/2011; , ISBN: 978-953-307-229-6
• Source

  Available from: PubMed Central

  Article: A network-based biomarker approach for molecular investigation and diagnosis of lung cancer.

  Yu-Chao Wang, Bor-Sen Chen
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  ABSTRACT: Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs). In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.
  BMC Medical Genomics 01/2011; 4:2. · 3.69 Impact Factor
• Article: Robust model matching design methodology for a stochastic synthetic gene network.

  Bor-Sen Chen, Chia-Hung Chang, Yu-Chao Wang, Chih-Hung Wu, Hsiao-Ching Lee
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  ABSTRACT: Synthetic biology has shown its potential and promising applications in the last decade. However, many synthetic gene networks cannot work properly and maintain their desired behaviors due to intrinsic parameter variations and extrinsic disturbances. In this study, the intrinsic parameter uncertainties and external disturbances are modeled in a non-linear stochastic gene network to mimic the real environment in the host cell. Then a non-linear stochastic robust matching design methodology is introduced to withstand the intrinsic parameter fluctuations and to attenuate the extrinsic disturbances in order to achieve a desired reference matching purpose. To avoid solving the Hamilton-Jacobi inequality (HJI) in the non-linear stochastic robust matching design, global linearization technique is used to simplify the design procedure by solving a set of linear matrix inequalities (LMIs). As a result, the proposed matching design methodology of the robust synthetic gene network can be efficiently designed with the help of LMI toolbox in Matlab. Finally, two in silico design examples of the robust synthetic gene network are given to illustrate the design procedure and to confirm the robust model matching performance to achieve the desired behavior in spite of stochastic parameter fluctuations and environmental disturbances in the host cell.
  Mathematical biosciences 01/2011; 230(1):23-36. · 1.30 Impact Factor
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  Available from: PubMed Central

  Article: On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach.

  Bor-Sen Chen, Ying-Po Lin
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  ABSTRACT: In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network's evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective.
  Evolutionary bioinformatics online 01/2011; 7:201-33. · 1.23 Impact Factor
• Article: A Fuzzy Approach for Robust Reference-Tracking-Control Design of Nonlinear Distributed Parameter Time-Delayed Systems and Its Application

  Yu-Te Chang, Bor-Sen Chen
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  ABSTRACT: This paper addresses the robust reference-tracking-control problem for nonlinear distributed parameter systems (NDPSs) with time delays, external disturbances, and measurement noises. The NDPS is measured at several sensor locations for output-feedback tracking control. A fuzzy-spatial state-space model derived via finite-difference approach is introduced to represent the nonlinear distributed parameter time-delayed system. Thus, we use a fuzzy interpolation method with several local linear systems to approximate the nonlinear system and employ the finite-difference method to approximate the partial differential operators in fuzzy-spatial state-space model. Based on this model, a robust fuzzy-observer-based reference-tracking controller is proposed to control the NDPS to track a desired reference trajectory. First, a 2-D tracking performance in a spatiotemporal domain is proposed for robust tracking design of nonlinear distributed parameter time-delayed systems. Then, an equivalent 1-D reference-tracking design is developed to simplify the design procedure, and the linear-matrix-inequality (LMI) technique is applied to solve the control gains and observer gains for the robust tracking-design problem via a systematic control-design procedure. Finally, a tracking-control-design example for the nervous system is given to confirm the proposed reference-tracking-control scheme of nonlinear distributed parameter time-delayed systems.
  IEEE Transactions on Fuzzy Systems 01/2011; · 4.26 Impact Factor
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  Available from: edu.tw

  Article: Robust Optimal Reference-Tracking Design Method for Stochastic Synthetic Biology Systems: T–S Fuzzy Approach

  Bor-Sen Chen, Chih-Hung Wu
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  ABSTRACT: At present, the development in the nascent field of synthetic gene networks is still difficult. Most newly created gene networks are nonfunctioning due to intrinsic parameter fluctuations, uncertain interactions with unknown molecules and external disturbances of intra and extracellular environments on the host cell. How to design a completely new gene network, that is to track some desired behaviors under these intrinsic and extrinsic disturbances on the host cell, is the most important topic in synthetic biology. In this study, the intrinsic parameter fluctuations, uncertain interactions with unknown molecules and environmental disturbances, are modeled into the nonlinear stochastic systems of synthetic gene networks in vivo. Four design specifications are introduced to guarantee the stochastic synthetic gene network, which can achieve robust optimal tracking of a desired reference model in spite of these intrinsic and extrinsic disturbances on the host cell. However, the robust optimal reference-tracking design problem of nonlinear synthetic gene networks is still hard to solve. In order to simplify the design procedure of the robust optimal nonlinear stochastic-tracking design for synthetic gene networks, the Takagi-Sugeno (T-S) fuzzy method is introduced to solve the nonlinear stochastic minimum-error-tracking design problem. Hence, the robust optimal reference-tracking design problem under four design specifications can be solved by the linear matrix inequality (LMI)-constrained optimization method using convex optimization techniques. Further, a simple design procedure is developed for synthetic gene networks to meet the four design specifications to achieve robust optimal reference tracking. Finally, an eigenvalue-shifted design method is also proposed as an expedient scheme to improve the stochastic optimal-tracking design method of synthetic gene oscillators.
  IEEE Transactions on Fuzzy Systems 01/2011; · 4.26 Impact Factor
• Article: Robust MC-CDMA Channel Tracking for Fast Time-Varying Multipath Fading Channel

  Chang-Yi Yang, Bor-Sen Chen
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  ABSTRACT: An unscented Kalman filter (UKF)-based channel-tracking method is proposed for a fast time-varying multipath fading channel in a multicarrier code-division multiple-access (MC-CDMA) system. The mobile radio channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the channel gain are simultaneously estimated by the proposed method. One-step-ahead prediction can also be obtained during channel estimation. It is useful for the decision-directed channel-tracking design, particularly in the fast-fading channel. Meanwhile, the estimated parameters can enhance the minimum mean-square error (MMSE) equalizer for symbol detection. The simulation results show that the enhanced equalizer based on the proposed estimation algorithm performs much better than that based on the conventional channel estimators in symbol error rate.
  IEEE Transactions on Vehicular Technology 12/2010; · 1.92 Impact Factor
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  Available from: nthu.edu.tw

  Article: Robust observer-based tracking control of hodgkin-huxley neuron systems under environmental disturbances.

  Bor-Sen Chen, Cheng-Wei Li
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  ABSTRACT: A nervous system consists of a large number of highly interconnected nerve cells. Nerve cells communicate by generation and transmission of short electrical pulses (action potential). In addition, membrane voltage is the only measurable state in nervous systems. A robust observer-based model reference tracking control is proposed for Hodgkin-Huxley (HH) neuron systems to generate a desired reference response in spite of environmental noises, uncertain initial values, and diffusion currents from other interconnected nerve cells. In order to simplify the robust tracking control design of nonlinear stochastic HH neuron systems, a fuzzy interpolation method is employed to interpolate several linear stochastic systems to approximate a nonlinear stochastic HH neuron system so that the nonlinear robust tracking control problem can be solved by the linear matrix inequality (LMI) technique with the help of Robust Control Toolbox in Matlab. The proposed robust observer-based tracking control scheme can provide new methods for desired action potential generation, suppression of oscillations, and blockage of action potential transmission under environmental noise and diffusion currents. These new methods are useful for patients with different neuron system dysfunctions. Finally, three simulation examples of tracking control of nervous systems are given to illustrate the design procedure and confirm the tracking performance of the proposed method.
  Neural Computation 12/2010; 22(12):3143-78. · 1.88 Impact Factor
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  Available from: InTech

  Chapter: Stochastic Game Theory Approach to Robust Synthetic Gene Network Design

  Bor-Sen Chen, Cheng-Wei Li, Chien-Ta Tu
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  ABSTRACT: Because the initial conditions and disturbances on the host cell are uncertain, to simplify the design problem, a robust synthetic biology design is formulated as a stochastic game problem in this study. The uncertain initial conditions and disturbances due to intrinsic and extrinsic molecular noises on the host cell are considered as a player maximizing the regulation error and the design parameters are considered as another player minimizing the regulation error. In order to avoid solving HJI in the stochastic game theory-based design problem, a T-S fuzzy interpolation method is introduced to simplify the design procedure of robust synthetic gene networks via only solving a set of LMIs, which can be efficiently solved by Robust Control Toolbox in Matlab. In our study, we can select the weighting matrix Q=diag([q11, q22, q33, q44]) which denotes the punishment on the corresponding tracking error x . If we only need to achieve a desired steady state xd4 (EYFP), we just assign a value to the fourth diagonal element q44 of the weighting matrix Q and set q11=q22= q33=0. The rest of states x1~x3 will not approach to the given steady state xd1~xd3 because of no any punishment. However, in this case, some infeasible steady states of x1, x2, and x3 may be obtained even an optimal x4 can be achieved. In this study, the desired steady states of x1, x2, and x3 are given because we can avoid obtaining infeasible steady states in x1, x2, and x3 when an optimal x4 is achieved. Further,
  09/2010; , ISBN: 978-953-307-132-9