Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

https://downloads.hindawi.com/archive/2013/897658.pdf

Biochemical Systems Theory: A Review

It is well known that protein-protein interaction (PPI) networks are typical evolving complex networks. Identification of important nodes has been an emerging popular topic in complex networks. Many indexes have been proposed to measure the importance of nodes in complex networks, such as degree, closeness, betweenness, k-shell, clustering coefficient, semi-local centrality, eigenvector centrality. Based on multivariate statistical analysis, through integrating the above indexes and further considering the appearances of nodes in network motifs, this paper aims at developing a new measure to characterize the structurally dominant proteins (SDP) in PPI networks. Moreover, we will further investigate the evolution of the defined dominant nodes in temporal evolving real-world and artificial PPI networks. Our results indicate that the constructed artificial networks have some similar statistical properties as those of the real-world evolving networks. In this case, the artificial PPI networks can be used to further investigate the above evolution characteristics of the real-world evolving networks. Simulation results reveal that SDP in the yeast PPI networks are evolutionary conserved, however, the undominant nodes evolve rapidly. Furthermore, PPI networks are very robust against random mutations, while fragile yet with certain robustness to targeted mutations on SDP. Our investigations shed some light on the future applications of the evolving characteristics of bio-molecular networks, such as reengineering of particular networks for technological, synthetic or pharmacological purposes.

Identification and Evolution of Structurally Dominant Nodes in Protein-Protein Interaction Networks

Biochemical regulatory networks including genes, proteins and other regulatory molecules suffer from internal parametrical fluctuations (thermal, transcriptional, and splicing) as well as external noises (environmental and intercellular). Robustness is an essential property of intracellular biochemical regulatory networks to attenuate the effects of internal fluctuation and external noise. In this study, several system control schemes are proposed for the robust circuit control design of stochastic linear and nonlinear biochemical regulatory networks. First, the robust stability of genetic and proteomic regulatory networks is discussed under internal fluctuations. Then, the filtering ability of external noises is analyzed for stochastic biochemical regulatory networks. For the case where a biochemical regulatory network is not sufficiently robust to tolerate internal fluctuation and does not have enough filtering ability to filter the external noise, how to improve the robustness and noise filtering ability of stochastic biochemical regulatory networks by engineered control mechanisms is also proposed via biochemical circuit design. The proposed robust gene circuit design principles have potential applications for robust biosynthetic network design. Finally, two design examples are given in-silico to illustrate the design procedure and to confirm the performance of the proposed robust circuit design method.

Robust Engineered Circuit Design Principles for Stochastic Biochemical Networks With Parameter Uncertainties and Disturbances

The sampling of the bacterial signal transduction is investigated for molecular communication (MC). It is assumed that the finite-duration amplitude modulated, i.e., pulse-amplitude modulated (PAM), concentration of a certain type of molecule is used for information transmission. The bacterial signaling pathway is modified to transduce the input molecules to the output signal, i.e., produce green fluorescent protein (GFP). The bacterial signal transduction is composed of a set of biochemical reactions which impose randomness on the response. Therefore, the input-output relation, the timing issues, and the noise effects for the bacteria response are characterized based on both analytical and experimental observations. Sampling schemes for the raw bacteria response are proposed based on the total response duration, the peak value, the ramp-up slope, and the ramp-down slope. Each sampling scheme is shown to be providing a one-to-one and monotonic function of the input. The sampling based on the ramp-up slope is shown to be statistically favorable for the detection of PAM molecular signals. Accordingly, the time interval selection and non-coherent sampling are studied for the efficient calculation of the ramp-up slope from the raw bacteria response. This work provides a basis for the sampling of the raw bacteria response and enables accurate detection of PAM molecular signals via bacterial response for MC and sensing applications.

Efficient Sampling of Bacterial Signal Transduction for Detection of Pulse-Amplitude Modulated Molecular Signals

The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

/pdf/on-the-interplay-between-entropy-and-robustness-of-gene-4sbjuyh5wy.pdf

On the interplay between entropy and robustness of gene regulatory networks

Based on the steady-state analyses of the synergism and saturation system (S-system) model, a robust control method is proposed for biochemical networks via feedback and feedforward biochemical circuits. Two robust biochemical circuit design schemes are developed. One scheme is to improve the system's structural stability so as to tolerate larger kinetic parameter variations, whereas the other is to compensate for the kinetic parameter variations to eliminate their effects. In addition, a multi-objective biochemical circuit design scheme is introduced for both the robust design against kinetic parameter variations and a desired sensitivity design to eliminate the effect of external disturbance simultaneously. The proposed robust circuit design schemes will provide a systematic method with potential applications in synthetic circuit design for biotechnological purpose and drug design purpose. Recent advances in both metabolic and genetic engineering have made the robust biochemical circuit control approach feasible through the design and implementation of synthetic biological networks amenable to mathematical modeling and quantitative analysis. Finally, several examples including the robust circuit design of the tricarboxylic acid cycle are used in silico to illustrate the design procedure and to confirm the performance of the proposed design method.

/pdf/on-the-robust-circuit-design-schemes-of-biochemical-networks-1duf0twv8s.pdf

On the Robust Circuit Design Schemes of Biochemical Networks: Steady-State Approach

It is demonstrated that the robust stabilization against additive nonlinear time-varying uncertainty presented by B.S. Chen and W.S. You (ibid., vol.AC-32, p.1131-5, Dec. 1987) is not just a sufficient but also a necessary condition. An additional necessary and sufficient condition that arises in the case of multiplicative uncertainty is also discussed. >

Chen Bor-Sen

Papers

On the Robust Circuit Design Schemes of Biochemical Networks: Steady-State Approach

Necessary and sufficient conditions for robust stabilization of an observer-based compensating system suffering nonlinear time-varying perturbation