Synthetic biology : modeling genetic circuits of quorum sensing system and biological logic gates
In the process of engineering a genetic circuit, modeling is the key step between design and fabrication. It helps to save time and resources by optimizing and predicting the behaviour of the synthetic circuit before actual construction. Of the many computational approaches available, the ODE modeli...
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Format: | Final Year Project |
Language: | English |
Published: |
2015
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Online Access: | http://hdl.handle.net/10356/63144 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | In the process of engineering a genetic circuit, modeling is the key step between design and fabrication. It helps to save time and resources by optimizing and predicting the behaviour of the synthetic circuit before actual construction. Of the many computational approaches available, the ODE modeling method was chosen for its simplicity and accuracy. In this project, a proposed ODE modeling approach was used to construct gene regulatory network models for the genetic circuits. The modeling process involves several steps; derivation of ODEs, retrieval of parameters, translation into Simulink block diagrams, simulation of model, validation of results, and optimization of model.
The genetic circuits modelled were a sensing device for quorum sensing and three logic gates: NOT, AND, NAND. For all the genetic circuits, the proposed modeling approach gave results that match the patterns of experiments but not the exact output values. The models were generally inaccurate and incapable of reflecting any component changes in the genetic circuit. On the contrary, the AND gate model successfully predicted experimental results and was demonstrated to be modular by connecting the output to a NOT gate module to produce a combinatorial NAND gate. The modeling approach also uncovered a practical application of the AND gate as a biological comparator and even as an indication sensor. Although the proposed approach is not able to construct accurate models, these results suggest that its predictive nature can be used to uncover trends and practical uses for genetic circuits and devices. |
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