References of "Wang, Z"
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See detailRobust stability of delayed genetic regulatory networks with different sources of uncertainties
Pan, Wei UL; Wang, Z.; Hu, J.

in Asian Journal of Control (2011), 13(5), 645-654

Gene regulation is inherently a stochastic process due to intrinsic and extrinsic noises which cause the fluctuations and uncertainties of kinetic parameters. On the other hand, time delays are usually ... [more ▼]

Gene regulation is inherently a stochastic process due to intrinsic and extrinsic noises which cause the fluctuations and uncertainties of kinetic parameters. On the other hand, time delays are usually inevitable due to different biochemical reactions in the genetic regulatory networks (GRNs) which are also affected by noises. Therefore, in this paper, we propose a GRN model that is subject to additive and multiplicative noises as well as time-varying delays. The time-varying delay is assumed to belong to an interval and no restriction on the derivative of the time-varying delay is needed, which allows the delay to be a fast time-varying function. Robust stochastic stability of such GRNs with disturbance attenuation is analyzed by applying the control theory and mathematical tools. Based on the Lyapunov method, new stability conditions are derived in the form of linear matrix inequalities that are dependent on the upper and lower bounds of time delays. An example is employed to illustrate the applicability and usefulness of the developed theoretical results. [less ▲]

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See detailOn multistability of delayed genetic regulatory networks with multivariable regulation functions
Pan, Wei UL; Wang, Z.; Gao, H. et al

in Mathematical Biosciences (2010), 228(1), 100-109

Many genetic regulatory networks (GRNs) have the capacity to reach different stable states. This capacity is defined as multistability which is an important regulation mechanism. Multiple time delays and ... [more ▼]

Many genetic regulatory networks (GRNs) have the capacity to reach different stable states. This capacity is defined as multistability which is an important regulation mechanism. Multiple time delays and multivariable regulation functions are usually inevitable in such GRNs. In this paper, multistability of GRNs is analyzed by applying the control theory and mathematical tools. This study is to provide a theoretical tool to facilitate the design of synthetic gene circuit with multistability in the perspective of control theory. By transforming such GRNs into a new and uniform mathematical formulation, we put forward a general sector-like regulation function that is capable of quantifying the regulation effects in a more precise way. By resorting to up-to-date techniques, a novel Lyapunov–Krasovskii functional (LKF) is introduced for achieving delay dependence to ensure less conservatism. New conditions are then proposed to ensure the multistability of a GRN in the form of linear matrix inequalities (LMIs) that are dependent on the delays. Our multistability conditions are applicable to several frequently used regulation functions especially the multivariable ones. Two examples are employed to illustrate the applicability and usefulness of the developed theoretical results. [less ▲]

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See detailMonostability and multistability of genetic regulatory networks with different types of regulation functions
Pan, Wei UL; Wang, Z; Gao, H. et al

in Nonlinear Analysis : Real World Applications (2010), 11(4), 31703185

Monostability and multistability are proven to be two important topics in synthesis biology and system biology. In this paper, both monostability and multistability are analyzed in a unified framework by ... [more ▼]

Monostability and multistability are proven to be two important topics in synthesis biology and system biology. In this paper, both monostability and multistability are analyzed in a unified framework by applying control theory and mathematical tools. The genetic regulatory networks (GRNs) with multiple time-varying delays and different types of regulation functions are considered. By putting forward a general sector-like regulation function and utilizing up-to-date techniques, a novel Lyapunov–Krasovskii functional is introduced for achieving delay dependence to ensure less conservatism. A new condition is then proposed for the general stability of a GRN in the form of linear matrix inequalities (LMIs) that are dependent on the upper and lower bounds of the delays. Our general stability conditions are applicable to several frequently used regulation functions. It is shown that the existing results for monostability of GRNs are special cases of our main results. Five examples are employed to illustrate the applicability and usefulness of the developed theoretical results. [less ▲]

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See detailRobust H∞ feedback control for uncertain stochastic delayed genetic regulatory networks with additive and multiplicative noise
Pan, Wei UL; Wang, Z.; Gao, H. et al

in International Journal of Robust and Nonlinear Control (2010), 20(18), 2093-2107

Noises are ubiquitous in genetic regulatory networks (GRNs). Gene regulation is inherently a stochastic process because of intrinsic and extrinsic noises that cause kinetic parameter variations and basal ... [more ▼]

Noises are ubiquitous in genetic regulatory networks (GRNs). Gene regulation is inherently a stochastic process because of intrinsic and extrinsic noises that cause kinetic parameter variations and basal rate disturbance. Time delays are usually inevitable due to different biochemical reactions in such GRNs. In this paper, a delayed stochastic model with additive and multiplicative noises is utilized to describe stochastic GRNs. A feedback gene controller design scheme is proposed to guarantee that the GRN is mean-square asymptotically stable with noise attenuation, where the structure of the controllers can be specified according to engineering requirements. By applying control theory and mathematical tools, the analytical solution to the control design problem is given, which helps to provide some insight into synthetic biology and systems biology. The control scheme is employed in a three-gene network to illustrate the applicability and usefulness of the design. [less ▲]

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See detailThe SOX10/Sox10 gene from human and mouse: sequence, expression, and transactivation by the encoded HMG domain transcription factor.
Pusch, C.; Hustert, E.; Pfeifer, D. et al

in Human Genetics (1998), 103(2), 115-23

The SOX genes form a gene family related by homology to the high-mobility group (HMG) box region of the testis-determining gene SRY. We have cloned and sequenced the SOX10 and Sox10 genes from human and ... [more ▼]

The SOX genes form a gene family related by homology to the high-mobility group (HMG) box region of the testis-determining gene SRY. We have cloned and sequenced the SOX10 and Sox10 genes from human and mouse, respectively. Both genes encode proteins of 466 amino acids with 98% sequence identity. Significant expression of the 2.9-kb human SOX10 mRNA is observed in fetal brain and in adult brain, heart, small intestine and colon. Strong expression of Sox10 occurs throughout the peripheral nervous system during mouse embryonic development. SOX10 shows an overall amino acid sequence identity of 59% to SOX9. Like SOX9, SOX10 has a potent transcription activation domain at its C-terminus and is therefore likely to function as a transcription factor. Whereas SOX9 maps to 17q, a SOX10 cosmid has previously been mapped by us to the region 22q13.1. Mutations in SOX10 have recently been identified as one cause of Waardenburg-Hirschsprung disease in humans, while a Sox10 mutation underlies the mouse mutant Dom, a murine Hirschsprung model. [less ▲]

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