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RESEARCH |
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PREFACE - INFORMATION
AND KNOWLEDGE |
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Five years ago, nearly one thousand
papers were published in biological journals and more
than one million base pairs were sequenced every day.
These figures have been exponentially increasing and today
there are numerous databases that hold all this information,
that make it almost impossible for research and analysis
to take place quickly and efficiently, which was the aim
of this information generation race all along. Moreover,
most of this information is usually only processed numbers
at best or raw data at worst. Without the meaning of this
information being elucidated all this resemble an encyclopaedia
written in a foreign language. |
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The case nowadays has become
that before we understand the complexity of life organisms
we must first understand and think in terms of information
technology. Computers are therefore extremely important
tools in the gadgetry of biologists. Gradually their potential
is being realised as they are more often being used as
an integral part of the discovery pipeline, rather than
just an elaborate calculator. Computers of the third millennium
can now perform billion calculations in a second and are
perfect candidates as master tools for the analysis of
large quantities of all the complex biological data being
generated experimentally. |
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INTRODUCTION TO BIOINFORMATICS |
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The integration of mathematical,
statistical and computer methods to analyse, manage and
process such biological, biochemical and biophysical data
is known as the field of Bioinformatics. |
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Academic programs are training
students in Bioinformatics by providing them with backgrounds
in molecular biology and in computer science, including
database design and analytical approaches. |
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For a more detailed definition
of Bioinformatics download
this PDF file here. |
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PHD RESEARCH |
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"Design
of gene/protein networks & presentation, modelling
and prediction of the dynamics of cellular signalling
pathways." |
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Signal transduction pathways
sense changes in the environment, convert these into signals
within the cell and ultimately stimulate a response. Hence,
signalling pathways are the means by which cells communicate
with their environment and with other cells. They determine
shape, size and motility of the cell, and control cell
division and nutrient intake. Overall, signalling pathways
constitute the control system that ensures proper function
of the cell in the context of the environment. Understanding
the way these signalling pathways operate individually
and in concert within the living cell is a major challenge
in post-genomic molecular biology and crucial for cancer
treatment, drug discovery, and genetic engineering. |
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Work in Anne Ridley's laboratory
has focussed on cell signalling pathways of the Rho protein
family, including the regulation of shear stress and mechanical
force responses in endothelial cells. Rho proteins are
known to play a key role in actin reorganisation (and
cell motility) and are implicated in the development of
cardiovascular diseases and cancer. Results obtained demonstrate
pronounced effects of biomechanical force on cell morphology.
Activation of Rho is very sensitive to biomechanical forces
resulting from continuous pressure of medium flow. Cells
undergo significant cytoskeletal rearrangement as a result
of differential activation of Rho proteins and the subsequent
protein/protein interactions of pathway components. |
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Partial knowledge
on how these signalling pathways function exists, however
it is not sufficient for a comprehensive understanding
of their operation. The complex molecular processes involved
are virtually impossible to analyse by cell biological
experiments alone. Furthermore, what is clearly lacking
is an insight into the dynamics of these signalling pathways
and their interaction with each other.
Mathematical and computational modelling of the complex
system can overcome these problems and can provide the
means for presenting a comprehensive and integrated view
on the operation of these signalling routes. Different
disciplines as molecular biology, genetics, computer science
and mathematics are essential for the understanding of
such complex biological systems. |
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In this project, a computational
model of the signal transduction processes will be built,
and predictions from the model will be compared to experimental
results. The aim will be to develop an understanding of
the importance of the different stages in the signal transduction
processes involving Rho, to explore the effects of and
sensitivity to changes at different stages, and, ultimately,
to explore how cytoskeletal rearrangement and cell motility
can be controlled. It is essential that the computational
modelling is closely linked to experimental work, with
the goal of developing an interaction between model and
experiment. |
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| Three main sections to this
project can be envisaged: |
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Collection of data and construction
of pathways
Published data from a variety of sources (literature,
Anne Ridley's lab, public databases, WWW resources) will
be used to identify the signal transduction pathways associated
with Rho activation. A static network of the relevant
proteins and their effectors will then be designed (Figure
1). Overlaps and unknowns will be highlighted and different
"versions" of pathways will be produced. |
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Mathematical modelling
Appropriate mathematical representations (Boolean logic,
ordinary differential equations, etc) for the processes
relevant to Rho will be chosen and used to characterise
and explore the dynamic behaviour of specific pathway
models of the network (Figure 2). Focus will not only
be on the most accurate models (which is often the case
in detailed dynamic modelling of small subsystems), but
also on the most relevant levels of modelling where prior
knowledge and known constraints can be represented (and
which over time can be refined and extended in different
ways). |
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Design and implementation of a relational
database
An innovative database will be created to store the different
models generated and allow the interactive access to detailed
model information (Chapter 2, Figure 3-4). The database
will specifically store information regarding interactions
between signalling components. This will include details
of dynamic behaviour (kinetic data), reaction conditions,
and other information that can be used either for the
modelling or to guide further experimental research.
The relational database will be designed, implemented
and integrated with a user-friendly graphic user interface.
Appropriate software may be added to aid the visualisation
and therefore understanding of the different models by
the end user.
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RESEARCH AREAS: |
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Systems
Biology |
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Networks |
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Database |
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Previous
Projects |
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