Analiza in načrtovanje gensko regulatornih omrežij kot sekvenčnih bioloških vezij

The thriving field of synthetic biology, merging biology with engineering, aims to develop novel biological systems for practical applications. One of the key objectives is also creating a biological computer using gene regulatory networks, similar to electronic components in traditional computing. This thesis explores the implementation of sequential biological circuits, specifically focusing on shift registers such as Serial-In Parallel-Out (SIPO), Parallel-In Serial-Out (PISO), and Linear Feedback Shift Registers (LFSR), in the context of gene regulatory networks. These registers are developed in Python as independent models, and their functionality is demonstrated using Jupyter Notebook. Through computational modeling and experiments, the biological registers accurately reproduce digital logic behaviors, including robust state transitions and memory functions. Validation against digital reference models shows high fidelity of these synthetic circuits. Parameter optimization using genetic algorithms further improves performance, while global sensitivity analysis highlights key parameters essential for robustness and reliable operation. The thesis also demonstrates the use of a biological clock oscillator (repressilator) to synchronize circuit activity, supporting the feasibility of programmable sequential logic in living cells. This work establishes a framework for precise control and optimization of multi-stage memory circuits, advancing the development of programmable biological circuits.