Publications
154 results found
Kulkarni VV, Stan GB, Raman K, 2014, A systems theoretic approach to systems and synthetic biology i: Models and system characterizations, ISBN: 9789401790406
The complexity of biological systems has intrigued scientists from many disciplines and has given birth to the highly influential field of systems biology wherein a wide array of mathematical techniques, such as flux balance analysis, and technology platforms, such as next generation sequencing, is used to understand, elucidate, and predict the functions of complex biological systems. More recently, the field of synthetic biology, i.e., de novo engineering of biological systems, has emerged. Scientists from various fields are focusing on how to render this engineering process more predictable, reliable, scalable, affordable, and easy. Systems and control theory is a branch of engineering and applied sciences that rigorously deals with the complexities and uncertainties of interconnected systems with the objective of characterising fundamental systemic properties such as stability, robustness, communication capacity, and other performance metrics. Systems and control theory also strives to offer concepts and methods that facilitate the design of systems with rigorous guarantees on these properties. Over the last 100 years, it has made stellar theoretical and technological contributions in diverse fields such as aerospace, telecommunication, storage, automotive, power systems, and others. Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology. Volume I provides a panoramic view that illustrates the potential of such mathematical methods in systems and synthetic biology. Recent advances in systems and synthetic biology have clearly demonstrated the benefits of a rigorous and systematic approach rooted in the principles of systems and control theory - not only does it lead to exciting insights and discoveries but it also reduces the inordinately lengthy trial-and-error process of wet-lab experiment
Hamadeh A, Gonçalves J, Stan GB, 2014, Analysis of synchronizing biochemical networks via incremental dissipativity, A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, Pages: 117-139, ISBN: 9789401790468
Synchronization, defined in a broad sense, is the phenomenon in which communicating agents coordinate outputs. The abundance of examples of this process in nature and engineering has led to its becoming an active sub-area of research in networks theory, as evidenced by the multitude of publications on the subject [4].
Kulkarni VV, Stan GB, Raman K, 2014, A systems theoretic approach to systems and synthetic biology ii: Analysis and design of cellular systems, ISBN: 9789401790468
The complexity of biological systems has intrigued scientists from many disciplines and has given birth to the highly influential field of systems biology wherein a wide array of mathematical techniques, such as flux balance analysis, and technology platforms, such as next generation sequencing, is used to understand, elucidate, and predict the functions of complex biological systems. More recently, the field of synthetic biology, i.e., de novo engineering of biological systems, has emerged. Scientists from various fields are focusing on how to render this engineering process more predictable, reliable, scalable, affordable, and easy. Systems and control theory is a branch of engineering and applied sciences that rigorously deals with the complexities and uncertainties of interconnected systems with the objective of characterising fundamental systemic properties such as stability, robustness, communication capacity, and other performance metrics. Systems and control theory also strives to offer concepts and methods that facilitate the design of systems with rigorous guarantees on these properties. Over the last 100 years, it has made stellar theoretical and technological contributions in diverse fields such as aerospace, telecommunication, storage, automotive, power systems, and others. Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology. Volume II contains chapters contributed by leading researchers in the field of systems and synthetic biology that concern modeling physiological processes and bottom-up constructions of scalable biological systems. The modeling problems include characterisation and synthesis of memory, understanding how homoeostasis is maintained in the face of shocks and relatively gradual perturbations, understanding the functioning and robustness of biological clocks suc
Pan W, Sootla A, Stan G-B, 2014, Distributed Reconstruction of Nonlinear Networks: An ADMM Approach, IFAC PAPERSONLINE, Vol: 47, Pages: 3208-3213, ISSN: 2405-8963
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- Citations: 1
Tomazou M, 2014, Towards light based dynamic control of synthetic biological systems
Algar RJR, Ellis T, Stan G-B, 2014, Modelling essential interactions between synthetic genes and their chassis cell, 53rd IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 5437-5444, ISSN: 0743-1546
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- Citations: 12
O'Clery N, Yuan Y, Stan G-B, et al., 2013, Observability and coarse graining of consensus dynamics through the external equitable partition, PHYSICAL REVIEW E, Vol: 88, ISSN: 1539-3755
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- Citations: 48
Algar R, Ellis T, Stan G-B, 2013, Modelling the burden caused by gene expression: an in silico investigation into the interactions between synthetic gene circuits and their chassis cell
In this paper we motivate and develop a model of gene expression for the purpose of studying the interaction between synthetic gene circuits and the chassis cell within which they are inserted. This model focuses on the translational aspect of gene expression as this is where the literature suggests the crucial interaction between gene expression and shared resources lies.
Arpino JAJ, Hancock EJ, Anderson J, et al., 2013, Tuning the dials of Synthetic Biology, Microbiology-Sgm, Vol: 159, Pages: 1236-1253, ISSN: 1465-2080
Wright O, Stan G-B, Ellis T, 2013, Building-in biosafety for synthetic biology, MICROBIOLOGY-SGM, Vol: 159, Pages: 1221-1235, ISSN: 1350-0872
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- Citations: 82
Yuan Y, Stan G-B, Shi L, et al., 2013, Decentralised minimum-time consensus, AUTOMATICA, Vol: 49, Pages: 1227-1235, ISSN: 0005-1098
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- Citations: 88
Papadimitriou KI, Stan G-B, Drakakis EM, 2013, Systematic computation of non-linear cellular and molecular dynamics with low-power cytomimetic circuits: A simulation study, PLoS ONE, Vol: 8, ISSN: 1932-6203
This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented.
Stan G-B, 2013, A century of revolution in bioengineering, BIOFUTUR, Pages: 38-39, ISSN: 0294-3506
Pan W, Yuan Y, Sandberg H, et al., 2013, Real-time Fault Diagnosis for Large-Scale Nonlinear Power Networks, 52nd IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 2340-2345, ISSN: 0743-1546
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- Citations: 5
Sootla A, Strelkowa N, Ernst D, et al., 2013, On periodic reference tracking using batch-mode reinforcement learning with application to gene regulatory network control., Publisher: IEEE, Pages: 4086-4091
Sootla A, Strelkowa N, Ernst D, et al., 2013, Toggling a Genetic Switch Using Reinforcement Learning, 9th French Meeting on Planning, Decision Making and Learning
Lugagne JB, Oyarzún DA, Stan GB, 2013, Stochastic simulation of enzymatic reactions under transcriptional feedback regulation, Proceedings of the European Control Conference, Pages: 3646-3651
Markides CN, Osuolale A, Solanki R, et al., 2013, Nonlinear Heat Transfer Processes in a Two-Phase Thermofluidic Oscillator, Applied Energy
A two-phase thermofluidic oscillator was recently reported as being capable of undergoing sustained operation when a constant and low temperature difference is applied to the device, which consists of a network of tubes, compartments and two heat exchanger blocks. Within this arrangement a working fluid undergoes thermodynamic property oscillations that describe a heat engine cycle. Previous attempts to model the dynamic behaviour of this thermofluidic engine for performance predictions have been based on linear analyses. These have provided us with useful knowledge of the necessary minimum temperature difference for operation, and the resulting oscillation frequency and efficiency. However, experimental observations suggest a limit cycle operation associated exclusively with nonlinear systems. The present paper presents an effort to devise a nonlinear model for the device. Indicative results from this model are discussed, and the predictions are compared to those from the linear equivalents and experimental observations. The results reveal that although both linear and nonlinear models predict similar oscillation frequencies, the nonlinear model predicts lower exergetic efficiencies. This probably arises from the inability of the linear model to capture the saturation in the rate of heat exchange between the working fluid and the heat exchangers. The present effort aims to provide a better understanding of this device and to suggest improved design guidelines for increased efficiency and power density.
Vignoni A, Oyarzún DA, Pico J, et al., 2013, Control of protein concentrations in heterogeneous cell populations, Proceedings of the European Control Conference, Pages: 3633-3639
Kuntz J, Oyarzún DA, Stan GB, 2013, Model reduction of genetic-metabolic systems using timescale separation, System Theoretic Approaches to Systems and Synthetic Biology (to appear), Publisher: Springer-Verlag
Yuan Y, Stan G-B, Warnick S, et al., 2012, Minimal realization of the dynamical structure function and its application to network reconstruction
Network reconstruction, i.e., obtaining network structure from data, is acentral theme in systems biology, economics and engineering. In some previouswork, we introduced dynamical structure functions as a tool for posing andsolving the problem of network reconstruction between measured states. Whilerecovering the network structure between hidden states is not possible sincethey are not measured, in many situations it is important to estimate theminimal number of hidden states in order to understand the complexity of thenetwork under investigation and help identify potential targets formeasurements. Estimating the minimal number of hidden states is also crucial toobtain the simplest state-space model that captures the network structure andis coherent with the measured data. This paper characterizes minimal orderstate-space realizations that are consistent with a given dynamical structurefunction by exploring properties of dynamical structure functions anddeveloping an algorithm to explicitly obtain such a minimal realization.
Anderson J, Strelkowa N, Stan G-B, et al., 2012, Engineering and ethical perspectives in synthetic biology, EMBO Reports, Vol: 13, Pages: 584-590, ISSN: 1469-221X
Synthetic biology has emerged as an exciting and promising new research field, garnering significant attention from both the scientific community and the general public. This interest results from a variety of striking features: synthetic biology is a truly interdisciplinary field that engages biologists, mathematicians, physicists and engineers; its research focus is applied; and it has enormous potential to harness the power of biology to provide scientific and engineering solutions to a wide range of problems and challenges that plague humanity. However, the power of synthetic biology to engineer organisms with custom‐made functionality requires that researchers and society use this power safely and responsibly, in particular when it comes to releasing organisms into the environment. This creates new challenges for both the design of such organisms and the regulatory process governing their creation and use.
Parker KH, Alastruey J, Stan G-B, 2012, Arterial reservoir-excess pressure and ventricular work, MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, Vol: 50, Pages: 419-424, ISSN: 0140-0118
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- Citations: 49
Sootla A, Strelkowa N, Ernst D, et al., 2012, On Periodic Reference Tracking Using Batch-Mode Reinforcement Learning with Application to Gene Regulatory Network Control, submitted to Conf. Decision Control
In this paper, we consider the periodic referencetracking problem in the framework of batch-mode reinforcement learning, which studies methods for solving optimal control problems from the sole knowledge of a set of trajectories. In particular, we adapt an existing batch-mode reinforcement learning algorithm, known as Fitted Q iteration, to the periodic reference tracking problem. The presented periodic reference tracking algorithm explicitly exploits a priori knowledge of the future values of the reference trajectory and its periodicity. We discuss the properties of our approach and illustrate it onthe problem of reference tracking for a synthetic biology gene regulatory network known as the generalised repressilator. This system can produce decaying but long-lived oscillations, which makes it an interesting system for the tracking problem. In our companion paper submitted to this conference we also take a look at the regulation problem of the toggle switch system, where the main goal is to drive the systems states to a specific bounded region in the state space.
Hamadeh A, Stan G-B, Sepulchre R, et al., 2012, Global State Synchronization in Networks of Cyclic Feedback Systems, Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Pages: 478-483, ISSN: 0018-9286
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- Citations: 51
Pan W, Yuan Y, Goncalves JM, et al., 2012, Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach., Publisher: IEEE, Pages: 2334-2339
Adebayo J, Southwick T, Chetty V, et al., 2012, Dynamical Structure Function Identifiability Conditions Enabling Signal Structure Reconstruction, 51st IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 4635-4641, ISSN: 0743-1546
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- Citations: 22
Oyarzún DA, Stan GB, 2012, Synthetic gene circuits for metabolic control: design tradeoffs and constraints, Journal of the Royal Society Interface, Vol: 10
Oyarzun DA, Stan GB, 2012, Design constraints in an operon circuit for engineered control of metabolic networks, Proceedings of the 51st IEEE Conference on Decision and Control, Pages: 3608-3613
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