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I am working on analyzing time series gene expression and other high
throughput biological data.
Expression profiling allows biologists to investigate thousands
of genes simultaneously. Of particular interest are time series
expression datasets, which allow us to view not only a snapshot
of the activity in the cell, but also the temporal relationships
between different genes. We have developed a number of algorithms
which assist in analyzing the results of these experiments. Our
algorithms address issues ranging from
low level analysis (such as
missing values, alignment etc.) via
pattern recognition
(such as clustering) to high level analysis
(combining different data sources
and temporal genetic regulatory networks, such as the cell cycle
network shown to the right). See the papers below for complete
details.
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