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Theme one
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Computational Biology
We focus on the functional genomics and
proteomics (discovering
causal relationships and functional association among genes,
proteins, and other factors. |
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Microarray Bioinformatics
(1) Reduction of noise in microarray data; (2) sample
classification; (3) clustering analysis; (4) identification of
significant genes. |
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Mass Spectrometry and Proteomics
(1) MS data pre-processing: noise reduction, base-line
correction, robust peak identification and alignment; (2)
classification and clustering analysis; (3) identification of
biomarkers. |
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Data Integration and Analysis
In order to interrelate the experimental data by means of public
databases and knowledge, we aim to develop computer systems
which allow the browsing and visualisation of data whilst
ensuring that complex queries can be performed on back-end data
stores. |
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Theme two
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Systems Biology
We focus on the
gene regulatory networks and gene co-expression network: (1) the
construction of networks; and (2) the characterization of the
networks. |
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Gene Co-expression Network from multiple microarray datasets |
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Gene
regulatory networks |
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Network motif discovery and
dynamic modelling |
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Theme three
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Cancer
Bioinformatics
We focus on the identification of
sub-network that is signification to a specific cancer/disease,
and the characterisation and evaluation of the function of
sub-network. |
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