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:
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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
  Shin Ho PARK in s1, 2014
Molecular Systems Biology
 

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