2024-03-28T17:08:19Zhttps://www.tdx.cat/oai/requestoai:www.tdx.cat:10803/3960842018-02-01T01:00:18Zcom_10803_1col_10803_51
nam a 5i 4500
Cèl·lules
Células
Cells
Adaptació (Biologia)
Adaptación (Biología)
Adaptation (Biology)
Processos estocàstics
Procesos estocásticos
Stochastic processes
Dynamics of cellular decision making processes
[Barcelona] :
Universitat de Barcelona,
2016
Accés lliure
http://hdl.handle.net/10803/396084
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Palau Ortin, David,
autor
1 recurs en línia (186 pàgines)
Tesi
Doctorat
Universitat de Barcelona. Departament d'Estructura i Constituents de la Matèria
2016
Universitat de Barcelona. Departament d'Estructura i Constituents de la Matèria
Tesis i dissertacions electròniques
Ibañes Miguez, Marta,
supervisor acadèmic
Sancho, José M.,
supervisor acadèmic
TDX
Cells, either as unicellular organisms or as part of a tissue of a multicellular organism, can acquire different functions thanks to their capability of changing their expression state. The enzyme synthesis, cell division or cell differentiation are some examples of these functions. The turning on and off of them lie in the mechanisms by which cells are able to integrate the information they perceive from the environment. Frequently, cells exhibit different responses under the same stimulus or environment. These probabilistic processes, whose behaviours are not univocal, are known as "cellular decision making". We can classify these processes according to the range at which the decision is made. We denominate cell-autonomous decision those in which of each cell chooses its response independently of the choice of the other cells of the population. By contrast, if the decision is made collectively by the whole population, it is classified as non autonomous. This second type of decisions involve mechanisms of cell-to-cell communication that mediate in the choices the cells and so, some spatial distributions of the different cell states can arise.
The capability of cellular decision making processes of performing a variety of responses under a same signal is given by the multistability and the stochasticity of their dynamics. While multistability is underlain by the nonlinear interactions of the elements involved in genetic regulation, stochasticity arises from the discrete nature of biochemical reactions and the thermal fluctuations of the cellular environment. These two characteristics motivate the study of these processes from Systems Dynamics the point of view, by identifying cell states with system attractors.
This Thesis focuses on the study of the general dynamical mechanisms that control cellular decision making processes. The main goal is to connect the properties of the decision with the relevant dynamical behaviour of the system while it is being made.
We have analysed the properties of cellular decisions in two systems: a system with cell-autonomous dynamics, where cells choose their state regardless the choice of the others; and a system where the decision is made jointly by all the tissue. In this second system, cells interact through a cell-to-cell communication that takes place at first neighbours. From these interactions, different pattern solutions arise, where different different cell types are spatially distributed along the tissue. Finally, it has been analysed the role that a specific choice, whose probability value is well known, plays in the functionality of an organism. The chosen system to study these consequences has been a process of differentiation that the parasite that causes malaria in humans performs.
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