Luo, Jamie X. (2012) Functionality and sensing in Boolean networks. PhD thesis, University of Warwick.

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Abstract

The main theme of this thesis is investigating how a cell’s biological function
relates to the topology of its Gene Regulatory Network (GRN). In this context,
the limits a biological function places on evolution are examined and also whether
genetic networks can evolve the capacity to sense internal mutations. GRNs are
modelled using Threshold Boolean Networks (TBNs), abstracting away details so
that certain computational approaches become viable. For instance in Chapter 3, all
possible TBNs that attain a specified functional path (of the form {v(t)}T
t=0) through
the expression state space are exhaustively found from a possible 3N2
TBNs, where
N is the number of genes (nodes) in the network. This allows for the detailed
examination of the complete neutral evolutionary space of a given functional path.
It is demonstrated that the major quantities of interest, such as the connectivity
of this neutral space under point mutations, the mutational and noise robustness
of the TBNs in this space and even the number of networks all depend strongly
on the duration T of the paths. The neutral space is found to disintegrate rapidly
into disconnected components as T is increased. The effect of more exotic functional
forms is also investigated. Chapter 4 focuses on evolving networks which are sensitive
to deletion mutations. It is found that increased sensitivity is readily evolvable in
TBNs, with the networks evolving to be more topologically balanced (they possess a
similar number of excitatory and inhibitory interactions). Networks are only found
to achieve maximal sensitivity through attaining long limit cycles. The study of
sensitivity is extended to static populations of TBNs in Chapter 5 and the question
is asked about whether a population of cells can develop the capacity to sense the
presence of a mutant among them. The multicellular framework is also used to
investigate the effect of intercellular connectivity on the dynamics. It is found that
the greater the intercellular connectivity the more uniform the expression patterns
are between cells. Chapter 6 applies the general Ergodic Set (ES) [Ribeiro and
Kauffman, 2007] concept to stem cell differentiation and cancer. An alternative
hypothesis to that in [Serra et al., 2010] is proposed about how to model stem cell
differentiation using ESs. Coupled with results from Chapter 4, I suggest that under
this new hypothesis, pluripotent stem cells will correspond to more sensitive TBNs
and that differentiated stem cells will correspond to more robust TBNs.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	Q Science > QH Natural history > QH301 Biology
Library of Congress Subject Headings (LCSH):	Genetic regulation -- Mathematical models, Cell physiology
Official Date:	2012
Dates:	Date Event 2012 Submitted
Institution:	University of Warwick
Theses Department:	Centre for Complexity Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Turner, Matthew S.
Sponsors:	Engineering and Physical Sciences Research Council (EPSRC) (EP/E501311/1, EP/I005439/1)
Extent:	v, 106 leaves : ill., charts
Language:	eng

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