Time series expression experiments are an increasingly popular method for
studying a wide range of biological systems.
However, when analyzing these experiments researchers face many new
computational challenges. Algorithms that are specifically designed
for time series experiments are required so that we can take advantage of
their unique features (such as the ability to infer causality from the
temporal response pattern) and address the unique problems they raise (for
example, handling the different non uniform sampling rates).
In this talk I will discuss the current research in this area. I will
present problems and (partial) solutions in a number of different analysis
levels ranging from experimental design to the data analysis and to systems
biology. The main goal of this talk is to expose you to the wide range of
computational problems that arise when analyzing time series expression
data. Thus, the talk will be self contained and no prior biological
knowledge will be required or assumed.
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Pradeep Ravikumar Last modified: Fri Mar 19 15:41:49 EST 2004