Abstract
We propose a molecular-level control system view of the gene mutations in DNA replication from the finite field concept. By treating DNA sequences as state variables, chemical mutagens and radiation as control inputs, one cell cycle as a step increment, and the measurements of the resulting DNA sequence as outputs, we derive system equations for both deterministic and stochastic discrete-time, finite-state systems of different scales. Defining the cost function as a summation of the costs of applying mutagens and the off-trajectory penalty, we solve the deterministic and stochastic optimal control problems by dynamic programming algorithm. In addition, given that the system is completely controllable, we find that the global optimum of both base-to-base and codon-to-codon deterministic mutations can always be achieved within a finite number of steps.
Highlights
Systems biology is an emerging academic field aiming at system-level understanding of biological systems
Identifying related components and their interactions, gathering qualitative and quantitative information about the system’s evolution under different circumstances, achieving the desired outputs by controlling the input with appropriate definitions of inputs and outputs of the system, and reconstructing analogous systems by eliminating the undesired properties are four essential steps in systems biology done by collaboration among engineers, biologists, and doctors
Biological systems can be divided into three levels: the molecular level, cellular level, and tissue level, analogous to the part, individual, and group, respectively
Summary
Systems biology is an emerging academic field aiming at system-level understanding of biological systems. A system-level understanding of a biological system can be derived from insight into four key properties: (1) the system’s structure, (2) the system dynamics, (3) the control method, and (4) the design method [2]. Identifying related components and their interactions, gathering qualitative and quantitative information about the system’s evolution under different circumstances, achieving the desired outputs by controlling the input with appropriate definitions of inputs and outputs of the system, and reconstructing analogous systems by eliminating the undesired properties are four essential steps in systems biology done by collaboration among engineers, biologists, and doctors. Run simulations, and predict the system behaviors. Control engineers revise and verify the models by comparing the predictions and experimental results
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