A Supervisory Control Theory Approach to Control Gene Regulatory Networks

Baldissera, Fabio L.; Cury, J.E.R.; Raisch, Jörg

doi:10.1109/tac.2015.2422411

Cited by 17 publications

(15 citation statements)

References 45 publications

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“…This assumption is not unrealistic and there are indeed reports in literature that provide support to it [30,31]. In a previous work, nevertheless, we dealt also with the more general case, when not all the events in Σ can be preempted [11].…”

Section: B Enlarging the Plant Model To Encompass The Control Inputsmentioning

confidence: 95%

“…In previous works, we showed, first qualitatively [10] and later more rigorously [11], how one could model and control gene regulatory networks whose dynamics are amenable to a discrete-event representation. In these cases, we assumed that: a) genes have boolean states; and b) it is possible to "program" synthetic genes and insert them in the cell to be controlled, in a way that these genes realize the control actions prescribed by the mathematical formulation of the supervisor.…”

Section: Modeling and Control Of Gene Network A Overviewmentioning

confidence: 99%

“…It is important to stress that the following rules are only a shortcut to obtain G hi . They are, in fact, the result of a procedure that was first laid out in [10] and later thoroughly and formally developed for the general case in [11]. It involves: a) enlarging the automaton G with the model of the synthetic gene layer; and, then, b) building an abstraction, based on state aggregation, to obtain G hi .…”

Section: B Enlarging the Plant Model To Encompass The Control Inputsmentioning

confidence: 99%

“…The admissible control inputs for this enriched case (where events can be, not only disabled but also forced by S), as well as the necessary and sufficient conditions for the existence of a supervisor S that brings the plant G hi from x 0 to X m , were laid out in our previous work [11]. In this paper, we shall keep this discussion in a more intuitive level, to focus on the main ideas we want to convey.…”

Section: Supervisor Synthesis Realization and Motivation For Thementioning

confidence: 99%

“…In previous works, we showed how ideas from Supervisory Control Theory (SCT) could be applied to solve the state attraction problem, which consists of guiding a cell from an initial state to some prespecified target state, keeping the system at this state indefinitely [10,11]. There, we assumed that: a) the plant consists of a gene regulatory network that can be abstracted by a discrete-event model; and b) the controller is implemented by synthetic genes that are inserted in the cell to close the loop.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Optimality in the control of gene regulatory networks

Baldissera

Cury

2014

53rd IEEE Conference on Decision and Control

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Controlling the behavior of intracellular networks has many important applications in Biotechnology and Medicine. In a previous work, we showed how the ideas from Supervisory Control Theory could be used to solve the state attraction problem applied to biological cells, i.e. guiding a cell from an initial state to some target state. The devised supervisor is then implemented by means of synthetic genes that are inserted in the cell. In this paper, we borrow ideas from Optimal Supervisory Control Theory to obtain supervisors that minimize an important metric associated with the problem of controlling the behavior of intracellular networks, namely, the minimization of the energy consumed for protein synthesis along the path from the initial to the target state.

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Section: B Enlarging the Plant Model To Encompass The Control Inputsmentioning

confidence: 95%

Section: Modeling and Control Of Gene Network A Overviewmentioning

confidence: 99%

Section: B Enlarging the Plant Model To Encompass The Control Inputsmentioning

confidence: 99%

Section: Supervisor Synthesis Realization and Motivation For Thementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimality in the control of gene regulatory networks

Baldissera

Cury

2014

53rd IEEE Conference on Decision and Control

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Masked observation for majority‐based control of a democratic progress model in the framework of discrete event systems

Park

Yang

2020

Asian Journal of Control

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This paper addresses a simple democratic progress model represented by a discrete-event system (DES) and the influence of information accessibility on the progressiveness of the model. Each agent makes a decision according to its selfish criterion, and the final decision for the progress or regression of the system is done by the majority rule based on individual decisions of agents. We first present the conditions for the closed-loop system to be progressive or regressive under full observation where every agent can observe all the states. Then we focus on the masked observation problem, namely, whether the progressiveness of the closed-loop behavior can be changed by restricting the information accessibility of agents that are characterized by their masks. Especially, we show that due to the elite class, the regressive closed-loop system can never be transformed into progressive regardless of mask design, which conforms to the feature of modern democracy.

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