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Cell signaling: a systems approach

Melke, Pontus LU (2010)
Abstract
All higher functions of the cell are dependent on cell signaling. It is the way of the cell to obtain information

about the world surrounding it. By getting information on e.g. temperature, glucose concentrations, or the

density of neighboring cells, the cell can make decisions on how to optimally act given the supplied information.

Even though cells are very different, some of the basic mechanisms governing the signaling are the same

everywhere – from the most simple single-cellular bacteria to the cells we find in our bodies.

In this thesis we will study cell signaling in three different types of cells: in Paper I we study the TGF-β pathway

in endothelial mammal cells, in Paper II and... (More)
All higher functions of the cell are dependent on cell signaling. It is the way of the cell to obtain information

about the world surrounding it. By getting information on e.g. temperature, glucose concentrations, or the

density of neighboring cells, the cell can make decisions on how to optimally act given the supplied information.

Even though cells are very different, some of the basic mechanisms governing the signaling are the same

everywhere – from the most simple single-cellular bacteria to the cells we find in our bodies.

In this thesis we will study cell signaling in three different types of cells: in Paper I we study the TGF-β pathway

in endothelial mammal cells, in Paper II and Paper III the biofilm formation and quorum sensing of bacterial

cells, and in Paper IV plant stem cells. We use a combination of rate-equation models, mechanical cell-based

models, and statistical tools to study the dynamics of these networks. By this approach we can find and validate

hypotheses in cases where mere biological intuition is not enough. We can also indentify key components and

modules of the systems, and predict quantities not yet measured. This provides a work flow where the model

is set up to test hypotheses against available data, the model suggests new experiments which later can be used

to further improve the model. The approach of combining experimental data with mathematical modeling has

proven to be very fruitful for the understanding of many biological systems. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Koumoutsakos, Petros, ETH Zurich
organization
publishing date
type
Thesis
publication status
published
subject
defense location
Sal F, Sölvegatan 14A
defense date
2010-03-15 10:15
ISBN
978-91-628-8035-4
language
English
LU publication?
yes
id
7590e436-650a-45d5-9f5a-6a2b2bf78b46 (old id 1544630)
date added to LUP
2010-02-17 09:19:37
date last changed
2016-09-19 08:45:15
@misc{7590e436-650a-45d5-9f5a-6a2b2bf78b46,
  abstract     = {All higher functions of the cell are dependent on cell signaling. It is the way of the cell to obtain information<br/><br>
about the world surrounding it. By getting information on e.g. temperature, glucose concentrations, or the<br/><br>
density of neighboring cells, the cell can make decisions on how to optimally act given the supplied information.<br/><br>
Even though cells are very different, some of the basic mechanisms governing the signaling are the same<br/><br>
everywhere – from the most simple single-cellular bacteria to the cells we find in our bodies.<br/><br>
In this thesis we will study cell signaling in three different types of cells: in Paper I we study the TGF-β pathway<br/><br>
in endothelial mammal cells, in Paper II and Paper III the biofilm formation and quorum sensing of bacterial<br/><br>
cells, and in Paper IV plant stem cells. We use a combination of rate-equation models, mechanical cell-based<br/><br>
models, and statistical tools to study the dynamics of these networks. By this approach we can find and validate<br/><br>
hypotheses in cases where mere biological intuition is not enough. We can also indentify key components and<br/><br>
modules of the systems, and predict quantities not yet measured. This provides a work flow where the model<br/><br>
is set up to test hypotheses against available data, the model suggests new experiments which later can be used<br/><br>
to further improve the model. The approach of combining experimental data with mathematical modeling has<br/><br>
proven to be very fruitful for the understanding of many biological systems.},
  author       = {Melke, Pontus},
  isbn         = {978-91-628-8035-4},
  language     = {eng},
  title        = {Cell signaling: a systems approach},
  year         = {2010},
}