master's thesis
Milenko Obradović (Author), Miha Moškon (Mentor), Miha Mraz (Co-mentor)

Abstract

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.

Keywords

gene regulatory networks;sequential biological circuits;synthetic biology;parameter optimization;sensitivity analysis;computer science;master's thesis;

Data

Language: English
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [M. Obradović]
UDC: 004:577.21(043.2)
COBISS: 247770371 Link will open in a new window
Views: 103
Downloads: 20
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Other data

Secondary language: Slovenian
Secondary title: Analiza in načrtovanje gensko regulatornih omrežij kot sekvenčnih bioloških vezij
Secondary abstract: Sintezna biologija je področje, ki združuje biologijo z inženirstvom in si prizadeva razviti nove biološke sisteme za praktične aplikacije. Eden izmed ključnih ciljev področja je ustvariti biološki računalnik z uporabo gensko regulatornih omrežij. V tem delu predstavimo izvedbo bioloških sekvenčnih bioloških vezij z gensko regulatornimi omrežij, s posebnim poudarkom na pomikalnih registrih, kot so register SIPO (angl. Serial-In Parallel-Out), register PISO (angl. Parallel-In Serial-Out) ter register LFSR (angl. Linear Feedback Shift Register). Izvedbo modelov registrov predstavimo v jeziku Python, njihovo delovanje pa analiziramo v okolju Jupyter Notebook. S pomočjo računalniškega modeliranja in simulacij ponazorimo pravilnost delovanj vzpostavljenih registrov. Validacijo vzpostavljenih vezij naredimo glede na referenčne modele. Dodatno izboljšamo delovanje modelov preko optimizacije parametrov z genetskimi algoritmi. Preko globalne analize občutljivosti identificiramo ključne parametre za robustno in zanesljivo delovanje predstavljenih vezij. Modele registrov dodatno razširimo z vključitvijo biološke ure za sinhronizacijo delovanja vezij. Izvedbo te demonstriramo z represilatorjem. To dodatno potrjuje izvedljivost programabilne sekvenčne logike v živih celicah. Predstavljeno delo demonstrira možnosti vzpostavitve in optimizacije večstopenjskih pomnilniških vezij ter predstavlja pomemben korak k razvoju programabilnih bioloških procesorjev.
Secondary keywords: genska regulacijska omrežja;sekvenčna biološka vezja;sintetična biologija;optimizacija parametrov;analiza občutljivosti;računalništvo;magisteriji;
Type (COBISS): Master's thesis/paper
Study programme: 1000471
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 1 spletni vir (1 datoteka PDF (XII, 71 str.))
ID: 27283027