Thesis

Thesis Topic Details

Topic ID:
 2721
Title:
 Molecular Systems Biology
Supervisor:
 Mike Bain
Research Area:
 Bioinformatics
Associated Staff
Assessor:
 Bruno Gaeta
Topic Details
Status:
 Active
Type:
 Research
Programs:
 CS CE BIOM BINF SE
Group Suitable:
 Yes
Industrial:
 No
Pre-requisites:
 --
Description:
 Molecular systems biology is a key area in post-genomics bioinformatics.
This has two main drivers.
First is the need to understand the behaviour
of cells at the systems-level, for example towards the goal of
drug design or industrial biotechnology.
Second is the increasing availability
of high-throughput technology such as microarrays generating
genome-wide data sets.
In this project, we are working according to a methodology adapted
from that of Leroy Hood at the Institute for Systems Biology:

1) assemble an integrated collection of data sets, prepared
in a format ready for computational inference, in collaboration
with biologists
2) apply techniques of computational inference, visualization, etc.
to generate executable ``models'' of biological activity
from the data
3) run the models on the data on a ``what-if'' basis to generate
testable predictions
4) run experiments designed to test these predictions and feed back the
results to stages 1 and 2, adding data sets and revising the
executable models

By computational inference we intend not only statistical algorithms
but logical, i.e., based on deduction and induction (machine learning).
Comments:
 --
Past Student Reports
  Yi Bei HUANG in s1, 2010
Molecular Systems Biology
  Jane SIVIENG in s2, 2009
Molecular Systems Biology
  Kevin Mathew ALEXANDER in s1, 2011
Molecular Systems Biology
 

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