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Статті в журналах з теми "Repressilator"

Автор: Grafiati

Опубліковано: 23 лютого 2024

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1

BULDÚ, JAVIER M., JORDI GARCÍA-OJALVO, ALEXANDRE WAGEMAKERS, and MIGUEL A. F. SANJUÁN. "ELECTRONIC DESIGN OF SYNTHETIC GENETIC NETWORKS." International Journal of Bifurcation and Chaos 17, no. 10 (October 2007): 3507–11. http://dx.doi.org/10.1142/s0218127407019275.

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Анотація:

We propose the use of nonlinear electronic circuits to study synthetic gene regulation networks. Specifically, we have designed two electronic versions of a synthetic genetic clock, known as the "repressilator," making use of appropriate electronic elements linked in the same way as the original biochemical system. We study the effects of coupling in a population of electronic repressilators, with the aim of observing coherent oscillations of the whole population. With these results, we show that this kind of nonlinear circuits can be helpful in the design and understanding of synthetic genetic networks.

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2

Oliveira, Samuel M. D., Jerome G. Chandraseelan, Antti Häkkinen, Nadia S. M. Goncalves, Olli Yli-Harja, Sofia Startceva, and Andre S. Ribeiro. "Single-cell kinetics of a repressilator when implemented in a single-copy plasmid." Molecular BioSystems 11, no. 7 (2015): 1939–45. http://dx.doi.org/10.1039/c5mb00012b.

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3

BUŞE, OLGUŢA, ALEXEY KUZNETSOV, and RODRIGO A. PÉREZ. "EXISTENCE OF LIMIT CYCLES IN THE REPRESSILATOR EQUATIONS." International Journal of Bifurcation and Chaos 19, no. 12 (December 2009): 4097–106. http://dx.doi.org/10.1142/s0218127409025237.

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The Repressilator is a genetic regulatory network used to model oscillatory behavior of more complex regulatory networks like the circadian clock. We prove that the Repressilator equations undergo a supercritical Hopf bifurcation as the maximal rate of protein synthesis increases, and find a large range of parameters for which there is a cycle.

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4

Ushikubo, T., W. Inoue, M. Yoda, and M. Sasai. "3P287 Stochastic Dynamics of Repressilator." Seibutsu Butsuri 44, supplement (2004): S261. http://dx.doi.org/10.2142/biophys.44.s261_3.

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5

Dukarić, Maša, Hassan Errami, Roman Jerala, Tina Lebar, Valery G. Romanovski, János Tóth, and Andreas Weber. "On three genetic repressilator topologies." Reaction Kinetics, Mechanisms and Catalysis 126, no. 1 (December 18, 2018): 3–30. http://dx.doi.org/10.1007/s11144-018-1519-5.

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6

Borg, Yanika, Ekkehard Ullner, Afnan Alagha, Ahmed Alsaedi, Darren Nesbeth, and Alexey Zaikin. "Complex and unexpected dynamics in simple genetic regulatory networks." International Journal of Modern Physics B 28, no. 14 (April 25, 2014): 1430006. http://dx.doi.org/10.1142/s0217979214300060.

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Анотація:

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

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7

Müller, Stefan, Josef Hofbauer, Lukas Endler, Christoph Flamm, Stefanie Widder, and Peter Schuster. "A generalized model of the repressilator." Journal of Mathematical Biology 53, no. 6 (September 2, 2006): 905–37. http://dx.doi.org/10.1007/s00285-006-0035-9.

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8

Kuznetsov, A., and V. Afraimovich. "Heteroclinic cycles in the repressilator model." Chaos, Solitons & Fractals 45, no. 5 (May 2012): 660–65. http://dx.doi.org/10.1016/j.chaos.2012.02.009.

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9

Knotz, Gabriel, Ulrich Parlitz, and Stefan Klumpp. "Synchronization of a genetic oscillator with the cell division cycle." New Journal of Physics 24, no. 3 (March 1, 2022): 033050. http://dx.doi.org/10.1088/1367-2630/ac5c16.

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Abstract Genetic circuits that control specific cellular functions are never fully insulated against influences of other parts of the cell. For example, they are subject to periodic modulation by the cell cycle through volume growth and gene doubling. To investigate possible effects of the cell cycle on oscillatory gene circuits dynamics, we modelled a simple synthetic genetic oscillator, the repressilator, and studied hallmarks of the resulting nonlinear dynamics. We found that the repressilator coupled to the cell cycle shows typical quasiperiodic motion with discrete Fourier spectra and windows in parameter space with synchronization of the two oscillators, with a devil’s stair case indicating the Arnold tongues of synchronization. In the case of identical parameters for the three genes of the repressilator and simultaneous gene duplication, we identify two classes of synchronization windows, symmetric and asymmetric, depending on whether the trajectories satisfy a discrete three-fold rotation symmetry, corresponding to cyclic permutation of the three genes. Unexpectedly changing the gene doubling time revealed that the width of the Arnold tongues is connected to that three-fold symmetry of the synchronization trajectories: non-simultaneous gene duplication increases the width of asymmetric synchronization regions, for some of them by an order of magnitude. By contrast, there is only a small or even a negative effect on the window size for symmetric synchronization. This observation points to a control mechanism of synchronization via the location of the genes on the chromosome.

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10

Glyzin, S., A. Kolesov, and N. Rozov. "On a mathematical model of a repressilator." St. Petersburg Mathematical Journal 33, no. 5 (August 24, 2022): 797–828. http://dx.doi.org/10.1090/spmj/1727.

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Анотація:

A mathematical model of the simplest three-link oscillatory gene network, the so-called repressilator, is considered. This model is a nonlinear singularly perturbed system of three ordinary differential equations. The existence and stability of a relaxation periodic solution invariant with respect to cyclic permutations of coordinates are investigated for this system.

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11

Verdugo, Anael. "Hopf Bifurcation Analysis of the Repressilator Model." American Journal of Computational Mathematics 08, no. 02 (2018): 137–52. http://dx.doi.org/10.4236/ajcm.2018.82011.

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12

Buzzi, Claudio A., and Jaume Llibre. "Hopf bifurcation in the full repressilator equations." Mathematical Methods in the Applied Sciences 38, no. 7 (April 23, 2014): 1428–36. http://dx.doi.org/10.1002/mma.3158.

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13

Potapov, Ilya, Boris Zhurov, and Evgeny Volkov. "Multi-stable dynamics of the non-adiabatic repressilator." Journal of The Royal Society Interface 12, no. 104 (March 2015): 20141315. http://dx.doi.org/10.1098/rsif.2014.1315.

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The assumption of the fast binding of transcription factors (TFs) to promoters is a typical point in studies of synthetic genetic circuits functioning in bacteria. Although the assumption is effective for simplifying the models, it becomes questionable in the light of in vivo measurements of the times TF spends searching for its cognate DNA sites. We investigated the dynamics of the full idealized model of the paradigmatic genetic oscillator, the repressilator, using deterministic mathematical modelling and stochastic simulations. We found (using experimentally approved parameter values) that decreases in the TF binding rate changes the type of transition between steady state and oscillation. As a result, this gives rise to the hysteresis region in the parameter space, where both the steady state and the oscillation coexist. We further show that the hysteresis is persistent over a considerable range of the parameter values, but the presence of the oscillations is limited by the low rate of TF dimer degradation. Finally, the stochastic simulation of the model confirms the hysteresis with switching between the two attractors, resulting in highly skewed period distributions. Moreover, intrinsic noise stipulates trains of large-amplitude modulations around the stable steady state outside the hysteresis region, which makes the period distributions bimodal.

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14

Volkov, E. I., and B. A. Zhurov. "Dynamic Behavior of an Isolated Repressilator with Feedback." Radiophysics and Quantum Electronics 56, no. 10 (March 2014): 697–707. http://dx.doi.org/10.1007/s11141-014-9474-0.

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15

Pett, J. Patrick, Matthew Kondoff, Grigory Bordyugov, Achim Kramer, and Hanspeter Herzel. "Co-existing feedback loops generate tissue-specific circadian rhythms." Life Science Alliance 1, no. 3 (June 2018): e201800078. http://dx.doi.org/10.26508/lsa.201800078.

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Gene regulatory feedback loops generate autonomous circadian rhythms in mammalian tissues. The well-studied core clock network contains many negative and positive regulations. Multiple feedback loops have been discussed as primary rhythm generators but the design principles of the core clock and differences between tissues are still under debate. Here we use global optimization techniques to fit mathematical models to circadian gene expression profiles for different mammalian tissues. It turns out that for every investigated tissue multiple model parameter sets reproduce the experimental data. We extract for all model versions the most essential feedback loops and find auto-inhibitions of period and cryptochrome genes,Bmal1–Rev-erb-αloops, and repressilator motifs as possible rhythm generators. Interestingly, the essential feedback loops differ between tissues, pointing to specific design principles within the hierarchy of mammalian tissue clocks. Self-inhibitions ofPerandCrygenes are characteristic for models of suprachiasmatic nucleus clocks, whereas in liver models many loops act in synergy and are connected by a repressilator motif. Tissue-specific use of a network of co-existing synergistic feedback loops could account for functional differences between organs.

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16

Bratsun, D. А., E. S. Lorgov, and A. O. Poluyanov. "On the repressilator stability with time-delayed gene expression." ВЕСТНИК ПЕРМСКОГО УНИВЕРСИТЕТА. ФИЗИКА, no. 2 (2018): 75–87. http://dx.doi.org/10.17072/1994-3598-2018-2-75-87.

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17

Pett, J. Patrick, Anja Korenčič, Felix Wesener, Achim Kramer, and Hanspeter Herzel. "Feedback Loops of the Mammalian Circadian Clock Constitute Repressilator." PLOS Computational Biology 12, no. 12 (December 12, 2016): e1005266. http://dx.doi.org/10.1371/journal.pcbi.1005266.

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18

Hellen, Edward H., Syamal K. Dana, Boris Zhurov, and Evgeny Volkov. "Electronic Implementation of a Repressilator with Quorum Sensing Feedback." PLoS ONE 8, no. 5 (May 2, 2013): e62997. http://dx.doi.org/10.1371/journal.pone.0062997.

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19

Bratsun, Dmitry Anatolievich, and Maksim Dmitrievich Buzmakov. "Repressilator with time-delayed gene expression. Part II. Stochastic description." Computer Research and Modeling 13, no. 3 (June 2021): 587–609. http://dx.doi.org/10.20537/2076-7633-2021-13-3-587-609.

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20

Bratsun, Dmitry Anatolievich, Eugeny Sergeevich Lorgov, and Alexander Olegovich Poluyanov. "Repressilator with time-delayed gene expression. Part I. Deterministic description." Computer Research and Modeling 10, no. 2 (April 2018): 241–59. http://dx.doi.org/10.20537/2076-7633-2018-10-2-241-259.

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21

Shum, Henry, Victor V. Yashin, and Anna C. Balazs. "Self-assembly of microcapsules regulated via the repressilator signaling network." Soft Matter 11, no. 18 (2015): 3542–49. http://dx.doi.org/10.1039/c5sm00201j.

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22

Deo, Ishan, and Krishnacharya Khare. "A simple electronic circuit demonstrating Hopf bifurcation for an advanced undergraduate laboratory." American Journal of Physics 90, no. 12 (December 2022): 908–13. http://dx.doi.org/10.1119/5.0062969.

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A nonlinear electronic circuit comprising of three nodes with a feedback loop is analyzed. The system has two stable states, a uniform state and a sinusoidal oscillating state, and it transitions from one to another by means of a Hopf bifurcation. The stability of this system is analyzed with nonlinear equations derived from a repressilator-like transistor circuit. The apparatus is simple and inexpensive, and the experiment demonstrates aspects of nonlinear dynamical systems in an advanced undergraduate laboratory setting.

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23

Hara, Shinji, Tetsuya Iwasaki, and Yutaka Hori. "Instability margin analysis for parametrized LTI systems with application to repressilator." Automatica 136 (February 2022): 110047. http://dx.doi.org/10.1016/j.automatica.2021.110047.

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24

Strelkowa, Natalja, and Mauricio Barahona. "Transient dynamics around unstable periodic orbits in the generalized repressilator model." Chaos: An Interdisciplinary Journal of Nonlinear Science 21, no. 2 (April 13, 2011): 023104. http://dx.doi.org/10.1063/1.3574387.

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25

Kim, Keun-Young, David Lepzelter, and Jin Wang. "Single molecule dynamics and statistical fluctuations of gene regulatory networks: A repressilator." Journal of Chemical Physics 126, no. 3 (January 21, 2007): 034702. http://dx.doi.org/10.1063/1.2424933.

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26

Agrawal, Vidit, Shivpal Singh Kang, and Sudeshna Sinha. "Realization of morphing logic gates in a repressilator with quorum sensing feedback." Physics Letters A 378, no. 16-17 (March 2014): 1099–103. http://dx.doi.org/10.1016/j.physleta.2014.02.015.

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27

Chandraseelan, Jerome G., Samuel M. D. Oliveira, Antti Häkkinen, Huy Tran, Ilya Potapov, Adrien Sala, Meenakshisundaram Kandhavelu, and Andre S. Ribeiro. "Effects of temperature on the dynamics of the LacI-TetR-CI repressilator." Molecular BioSystems 9, no. 12 (2013): 3117. http://dx.doi.org/10.1039/c3mb70203k.

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28

Glyzin, S. D., A. Yu Kolesov, and N. Kh Rozov. "Existence and stability of the relaxation cycle in a mathematical repressilator model." Mathematical Notes 101, no. 1-2 (January 2017): 71–86. http://dx.doi.org/10.1134/s0001434617010072.

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29

Pokhilko, Alexandra, Aurora Piñas Fernández, Kieron D. Edwards, Megan M. Southern, Karen J. Halliday, and Andrew J. Millar. "The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loops." Molecular Systems Biology 8, no. 1 (January 2012): 574. http://dx.doi.org/10.1038/msb.2012.6.

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30

Dilão, Rui. "The regulation of gene expression in eukaryotes: Bistability and oscillations in repressilator models." Journal of Theoretical Biology 340 (January 2014): 199–208. http://dx.doi.org/10.1016/j.jtbi.2013.09.010.

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31

TOKUDA, ISAO T., ALEXANDRE WAGEMAKERS, and MIGUEL A. F. SANJUÁN. "PREDICTING THE SYNCHRONIZATION OF A NETWORK OF ELECTRONIC REPRESSILATORS." International Journal of Bifurcation and Chaos 20, no. 06 (June 2010): 1751–60. http://dx.doi.org/10.1142/s0218127410026800.

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Анотація:

Synchronization of coupled oscillators is by now a very well studied subject. A large number of analytical and computational tools are available for the treatment of experimental results. This article focuses on a method recently proposed to construct a phase model from experimental data. The advantage of this method is that it extracts a phase model in a noninvasive manner without any prior knowledge of the experimental system. The aim of the present research is to apply this methodology to a network of electronic genetic oscillators. These electronic circuits mimic the dynamics of a synthetic genetic oscillator, called "repressilator", which is capable of synthesizing autonomous biological rhythms. The obtained phase model is shown to be capable of recovering the route leading to synchronization of genetic oscillators. The predicted onset point of synchronization agrees quite well with the experiment. This encourages further application of the present method to synthetic biological systems.

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32

Ayupova, N. B., V. P. Golubyatnikov, and M. V. Kazantsev. "On the existence of a cycle in an asymmetric model of a molecular repressilator." Numerical Analysis and Applications 10, no. 2 (April 2017): 101–7. http://dx.doi.org/10.1134/s199542391702001x.

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33

Rim, D. N., P. Cremades, and Pablo Federico Kaluza. "A simple electronic device to experiment with the Hopf bifurcation." Revista Mexicana de Física E 65, no. 1 (January 21, 2019): 58. http://dx.doi.org/10.31349/revmexfise.65.58.

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We present a simple low-cost electronic circuit that is able to show two different dynamical regimens with oscillations of voltages and with constant values of them. This device is designed as a negative feedback three-node network inspired in the genetic repressilator. The circuit's behavior is modeled by a system of differential equations which is studied in several different ways by applying the dynamical system formalism, making numerical simulations and constructing and measuring it experimentally. We find that the most important characteristics of the Hopf bifurcation can be found and controlled. Particularly, a resistor value plays the role of the bifurcation parameter, which can be easily varied experimentally. As a result, this system can be employed to introduce many aspects of a research in a real physical system and it enables us to study one of the most important kinds of bifurcation.

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34

Ayupova, N. B., and V. P. Golubyatnikov. "On the uniqueness of a cycle in an asymmetric three-dimensional model of a molecular repressilator." Journal of Applied and Industrial Mathematics 8, no. 2 (April 2014): 153–57. http://dx.doi.org/10.1134/s199047891402001x.

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35

Perez-Carrasco, Ruben, Chris P. Barnes, Yolanda Schaerli, Mark Isalan, James Briscoe, and Karen M. Page. "Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors." Cell Systems 6, no. 4 (April 2018): 521–30. http://dx.doi.org/10.1016/j.cels.2018.02.008.

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36

Glyzin, Sergey D., Andgey Yu Kolesov, and Nikolay Kh Rozov. "New Approach to Gene Network Modeling." Modeling and Analysis of Information Systems 26, no. 3 (September 28, 2019): 365–404. http://dx.doi.org/10.18255/1818-1015-2019-3-365-404.

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The article is devoted to the mathematical modeling of artificial genetic networks. A phenomenological model of the simplest genetic network called repressilator is considered. This network contains three elements unidirectionally coupled into a ring. More specifically, the first of them inhibits the synthesis of the second, the second inhibits the synthesis of the third, and the third, which closes the cycle, inhibits the synthesis of the first one. The interaction of the protein concentrations and of mRNA (message RNA) concentration is surprisingly similar to the interaction of six ecological populations — three predators and three preys. This allows us to propose a new phenomenological model, which is represented by a system of unidirectionally coupled ordinary differential equations. We study the existence and stability problem of a relaxation periodic solution that is invariant with respect to cyclic permutations of coordinates. To find the asymptotics of this solution, a special relay system is constructed. It is proved in the paper that the periodic solution of the relay system gives the asymptotic approximation of the orbitally asymptotically stable relaxation cycle of the problem under consideration.

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37

Skornyakov, Vladimir, Maria Skornyakova, Antonina Shurygina, and Pavel Skornyakov. "Finite-state discrete-time Markov chain models of gene regulatory networks." F1000Research 3 (September 12, 2014): 220. http://dx.doi.org/10.12688/f1000research.4669.1.

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In this study, Markov chain models of gene regulatory networks (GRN) are developed. These models make it possible to apply the well-known theory and tools of Markov chains to GRN analysis. A new kind of finite interaction graph called a combinatorial net is introduced to represent formally a GRN and its transition graphs constructed from interaction graphs. The system dynamics are defined as a random walk on the transition graph, which is a Markov chain. A novel concurrent updating scheme (evolution rule) is developed to determine transitions in a transition graph. The proposed scheme is based on the firing of a random set of non-steady-state vertices in a combinatorial net. It is demonstrated that this novel scheme represents an advance in asynchronicity modeling. The theorem that combinatorial nets with this updating scheme can asynchronously compute a maximal independent set of graphs is also proved. As proof of concept, a number of simple combinatorial models are presented here: a discrete auto-regression model, a bistableswitch, an Elowitz repressilator, and a self-activation model, and it is shown that these models exhibit well-known properties.

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38

Shum, Henry, and Anna C. Balazs. "Synthetic quorum sensing in model microcapsule colonies." Proceedings of the National Academy of Sciences 114, no. 32 (July 24, 2017): 8475–80. http://dx.doi.org/10.1073/pnas.1702288114.

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Biological quorum sensing refers to the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. Designing synthetic materials systems that exhibit quorum sensing-like behavior could enable the fabrication of devices with both self-recognition and self-regulating functionality. Herein, we develop models for a colony of synthetic microcapsules that communicate by producing and releasing signaling molecules. Production of the chemicals is regulated by a biomimetic negative feedback loop, the “repressilator” network. Through theory and simulation, we show that the chemical behavior of such capsules is sensitive to both the density and number of capsules in the colony. For example, decreasing the spacing between a fixed number of capsules can trigger a transition in chemical activity from the steady, repressed state to large-amplitude oscillations in chemical production. Alternatively, for a fixed density, an increase in the number of capsules in the colony can also promote a transition into the oscillatory state. This configuration-dependent behavior of the capsule colony exemplifies quorum-sensing behavior. Using our theoretical model, we predict the transitions from the steady state to oscillatory behavior as a function of the colony size and capsule density.

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39

YAMASHINO, Takafumi. "From a Repressilator-Based Circadian Clock Mechanism to an External Coincidence Model Responsible for Photoperiod and Temperature Control of Plant Architecture inArabodopsis thaliana." Bioscience, Biotechnology, and Biochemistry 77, no. 1 (January 23, 2013): 10–16. http://dx.doi.org/10.1271/bbb.120765.

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40

Narayanan, G., M. Syed Ali, Rajagopal Karthikeyan, Grienggrai Rajchakit, and Anuwat Jirawattanapanit. "Impulsive control strategies of mRNA and protein dynamics on fractional-order genetic regulatory networks with actuator saturation and its oscillations in repressilator model." Biomedical Signal Processing and Control 82 (April 2023): 104576. http://dx.doi.org/10.1016/j.bspc.2023.104576.

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41

Kosey, Dipali, and Shailza Singh. "Computational design of molecular motors as nanocircuits in Leishmaniasis." F1000Research 6 (January 31, 2017): 94. http://dx.doi.org/10.12688/f1000research.10701.1.

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Cutaneous leishmaniasis is the most common form of lesihmaniasis, caused by Leishmania major and is spread by the bite of a sandfly.This species infects the macrophages and dendritic cells Due to multi-drug resistance, there is a need for a new therapeutic technique. Recently, a novel molecular motor of Leishmania, Myosin XXI, was classified and characterized. In addition, the drug resistance in this organism has been linked with the overexpression of ABC transporters. Systems biology aims to study the simulation and modeling of natural biological systems whereas synthetic biology deals with building novel and artificial biological parts and devices Together they have contributed enormously to drug discovery, vaccine design and development, infectious disease detection and diagnostics. Synthetic genetic regulatory networks with desired properties, like toggling and oscillation have been proposed to be useful for gene therapy. In this work, a nanocircuit with coupled bistable switch – repressilator has been designed, simulated in the presence and absence of inducer, in silico, using Tinker Cell. When inducer is added, the circuit has been shown to produce reporter at high levels, which will impair the activity of Myosin XXI and ABC transporters. Validation of the circuit was also performed using GRENITS and BoolNet. The influence of inducer on the working of the circuit, i.e., the type of gene expression, response time delay, the steady states formed by the circuit and the quasipotential landscape of the circuit were performed. It was found that the addition of inducer reduced the response time delay in the graded type of gene expression and removed the multiple intermediate attractors of the circuit. Thus, the inducer increased the probability of the circuit to be present in the dominant stable state with high reporter concentration and hence the designed nanocircuit may be used for the treatment of leishmaniasis.

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42

Kosey, Dipali, and Shailza Singh. "Computational design of molecular motors as nanocircuits in Leishmaniasis." F1000Research 6 (August 3, 2017): 94. http://dx.doi.org/10.12688/f1000research.10701.2.

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Анотація:

Cutaneous leishmaniasis is the most common form of leishmaniasis, caused by Leishmania major and is spread by the bite of a sandfly.This species infects the macrophages and dendritic cells Due to multi-drug resistance, there is a need for a new therapeutic technique. Recently, a novel molecular motor of Leishmania, Myosin XXI, was classified and characterized. In addition, the drug resistance in this organism has been linked with the overexpression of ABC transporters. Systems biology aims to study the simulation and modeling of natural biological systems whereas synthetic biology deals with building novel and artificial biological parts and devices Together they have contributed enormously to drug discovery, vaccine design and development, infectious disease detection and diagnostics. Synthetic genetic regulatory networks with desired properties, like toggling and oscillation have been proposed to be useful for gene therapy. In this work, a nanocircuit with coupled bistable switch – repressilator has been designed, simulated in the presence and absence of inducer, in silico, using Tinker Cell. When inducer is added, the circuit has been shown to produce reporter at high levels, which will impair the activity of Myosin XXI and ABC transporters. Validation of the circuit was also performed using GRENITS and BoolNet. The influence of inducer on the working of the circuit, i.e., the type of gene expression, response time delay, the steady states formed by the circuit and the quasipotential landscape of the circuit were performed. It was found that the addition of inducer reduced the response time delay in the graded type of gene expression and removed the multiple intermediate attractors of the circuit. Thus, the inducer increased the probability of the circuit to be present in the dominant stable state with high reporter concentration and hence the designed nanocircuit may be used for the treatment of leishmaniasis.

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43

Yoda, M., and M. Sasai. "2P308 Stochastics dynamics of coupled repressilators." Seibutsu Butsuri 45, supplement (2005): S196. http://dx.doi.org/10.2142/biophys.45.s196_4.

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44

Potapov, Iliya Sergeevich, and Evgeny Izrailevich Volkov. "Dynamics analysis of coupled synthetic genetic repressilators." Computer Research and Modeling 2, no. 4 (December 2010): 403–18. http://dx.doi.org/10.20537/2076-7633-2010-2-4-403-418.

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45

Stankevich, N., and E. Volkov. "Evolution of quasiperiodicity in quorum-sensing coupled identical repressilators." Chaos: An Interdisciplinary Journal of Nonlinear Science 30, no. 4 (April 2020): 043122. http://dx.doi.org/10.1063/1.5140696.

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46

Garcia-Ojalvo, J., M. B. Elowitz, and S. H. Strogatz. "Modeling a synthetic multicellular clock: Repressilators coupled by quorum sensing." Proceedings of the National Academy of Sciences 101, no. 30 (July 15, 2004): 10955–60. http://dx.doi.org/10.1073/pnas.0307095101.

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47

Abrego, Luis, and Alexey Zaikin. "Integrated Information as a Measure of Cognitive Processes in Coupled Genetic Repressilators." Entropy 21, no. 4 (April 10, 2019): 382. http://dx.doi.org/10.3390/e21040382.

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Intercellular communication and its coordination allow cells to exhibit multistability as a form of adaptation. This conveys information processing from intracellular signaling networks enabling self-organization between other cells, typically involving mechanisms associated with cognitive systems. How information is integrated in a functional manner and its relationship with the different cell fates is still unclear. In parallel, drawn originally from studies on neuroscience, integrated information proposes an approach to quantify the balance between integration and differentiation in the causal dynamics among the elements in any interacting system. In this work, such an approach is considered to study the dynamical complexity in a genetic network of repressilators coupled by quorum sensing. Several attractors under different conditions are identified and related to proposed measures of integrated information to have an insight into the collective interaction and functional differentiation in cells. This research particularly accounts for the open question about the coding and information transmission in genetic systems.

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48

NAKAMURA, Tomohiko, Yutaka HORI, and Shinji HARA. "Hierarchical Modeling and Local Stability Analysis for Repressilators Coupled by Quorum Sensing." SICE Journal of Control, Measurement, and System Integration 7, no. 3 (2014): 133–40. http://dx.doi.org/10.9746/jcmsi.7.133.

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49

Ling, Guang, Zhi-Hong Guan, Ding-Xin He, Rui-Quan Liao, and Xian-He Zhang. "Stability and bifurcation analysis of new coupled repressilators in genetic regulatory networks with delays." Neural Networks 60 (December 2014): 222–31. http://dx.doi.org/10.1016/j.neunet.2014.08.012.

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50

Inagaki, Shiho, and Nathanael Aubert-Kato. "Controlling the Synchronization of Molecular Oscillators through Indirect Coupling." Micromachines 13, no. 2 (February 1, 2022): 245. http://dx.doi.org/10.3390/mi13020245.

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In this article, we study the coupling of a collection of molecular oscillators, called repressilators, interacting indirectly through enzymatic saturation. We extended a measure of autocorrelation to identify the period of the whole system and to detect coupling behaviors. We explored the parameter space of concentrations of molecular species in each oscillator versus enzymatic saturation, and observed regions of uncoupled, partially, or fully coupled systems. In particular, we found a region that provided a sharp transition between no coupling, two coupled oscillators, and full coupling. In practical applications, signals from the environment can directly affect parameters such as local enzymatic saturation, and thus switch the system from a coupled to an uncoupled regime and vice-versa. Our parameter exploration can be used to guide the design of complex molecular systems, such as active materials or molecular robot controllers.

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