This thesis focuses on Deterministic and Probabilistic Boolean Control Networks and their application to some specific Gene Regulatory Networks. At first, some introductory materials about Boolean Logic, Left Semi-tensor Product and Probability are presented in order to explain in detail the concepts of Boolean Networks, Boolean Control Networks, Probabilistic Boolean Networks and Probabilistic Boolean Control Networks. These networks can be modelled in state-space and their representation, obtained by means of the left semi-tensor product, is called algebraic form. Subsequently, the thesis concentrates on presenting the fundamental properties of these networks such as the classical Systems Theory properties of stability, reachability, controllability and stabilisation. Afterwards, the attention is drawn towards the comparison between deterministic and probabilistic boolean networks. Finally, two examples of Gene Regulatory Networks are modelled and analysed by means of a Boolean Network and a Probabilistic Boolean Network.

This thesis focuses on Deterministic and Probabilistic Boolean Control Networks and their application to some specific Gene Regulatory Networks. At first, some introductory materials about Boolean Logic, Left Semi-tensor Product and Probability are presented in order to explain in detail the concepts of Boolean Networks, Boolean Control Networks, Probabilistic Boolean Networks and Probabilistic Boolean Control Networks. These networks can be modelled in state-space and their representation, obtained by means of the left semi-tensor product, is called algebraic form. Subsequently, the thesis concentrates on presenting the fundamental properties of these networks such as the classical Systems Theory properties of stability, reachability, controllability and stabilisation. Afterwards, the attention is drawn towards the comparison between deterministic and probabilistic boolean networks. Finally, two examples of Gene Regulatory Networks are modelled and analysed by means of a Boolean Network and a Probabilistic Boolean Network.

Deterministic and Probabilistic Boolean Control Networks and their application to Gene Regulatory Networks

CHECH, ALBERTO
2021/2022

Abstract

This thesis focuses on Deterministic and Probabilistic Boolean Control Networks and their application to some specific Gene Regulatory Networks. At first, some introductory materials about Boolean Logic, Left Semi-tensor Product and Probability are presented in order to explain in detail the concepts of Boolean Networks, Boolean Control Networks, Probabilistic Boolean Networks and Probabilistic Boolean Control Networks. These networks can be modelled in state-space and their representation, obtained by means of the left semi-tensor product, is called algebraic form. Subsequently, the thesis concentrates on presenting the fundamental properties of these networks such as the classical Systems Theory properties of stability, reachability, controllability and stabilisation. Afterwards, the attention is drawn towards the comparison between deterministic and probabilistic boolean networks. Finally, two examples of Gene Regulatory Networks are modelled and analysed by means of a Boolean Network and a Probabilistic Boolean Network.
2021
Deterministic and Probabilistic Boolean Control Networks and their application to Gene Regulatory Networks
This thesis focuses on Deterministic and Probabilistic Boolean Control Networks and their application to some specific Gene Regulatory Networks. At first, some introductory materials about Boolean Logic, Left Semi-tensor Product and Probability are presented in order to explain in detail the concepts of Boolean Networks, Boolean Control Networks, Probabilistic Boolean Networks and Probabilistic Boolean Control Networks. These networks can be modelled in state-space and their representation, obtained by means of the left semi-tensor product, is called algebraic form. Subsequently, the thesis concentrates on presenting the fundamental properties of these networks such as the classical Systems Theory properties of stability, reachability, controllability and stabilisation. Afterwards, the attention is drawn towards the comparison between deterministic and probabilistic boolean networks. Finally, two examples of Gene Regulatory Networks are modelled and analysed by means of a Boolean Network and a Probabilistic Boolean Network.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/35590