Dealing with biological constraints in the synthesis of controllers for gene regulatory networks

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

doi:10.3182/20140824-6-za-1003.02434

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…For instance, supervisors that are implemented with fewer synthetic genes are preferable to those that need more genes, given that synthetic genes must be replicated during host cell division, thus consuming energy. Besides that, the design of synthetic genes should be kept as simple as possible, that is, with regulatory regions that can be achieved in practice (see for example the work in [33]). Finally, one could search for a solution that leads to the minimum possible intervention in the natural behavior of the network.…”

Section: Discussionmentioning

confidence: 99%

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: Discussionmentioning

confidence: 99%

Optimality in the control of gene regulatory networks

Baldissera

Cury

2014

53rd IEEE Conference on Decision and Control

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“…This control policy can be implemented by the activation of v s 1 at the macrostates 010 and 101, and by the activation of v s 3 at 110 and 111. In order to simplify the Boolean function that must be computed by the regulatory regions of synthetic genes, we may additionally impose the activation of v s 1 and v s 3 at other macrostates that do not belong to the closed-loop trajectory, according to ideas we described in [13]. Make then S hi (000) = S hi (001) = S hi (100) = {+u 1 } and S hi (100) = S hi (101) = {+u 3 }.…”

Section: A Deriving G and G Himentioning

confidence: 99%

Computing continuous control laws for gene regulatory networks within a discrete-event systems approach

Baldissera

Cury

2016

2016 13th International Workshop on Discrete Event Systems (WODES)

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Controlling the dynamics of intracellular networks has many important applications in Biotechnology and Medicine. In a previous work, we presented a method based on the Supervisory Control Theory to find a control law capable of guiding a given gene regulatory network from an initial state to some predefined target state. The controller was assumed to be implemented by synthetic genes. Our approach was entirely developed in the discrete-event domain. In this paper, we show that our ideas can also be employed to find continuous control laws for gene regulatory networks modeled by ordinary differential equations. Hence, we: a) enlarge the range of application of our initial ideas to encompass continuous models traditionally used by the Systems Biology community; and b) make it possible to refine the dynamic specifications of the synthetic genes that act as controllers.

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