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Microarrays
are costly, both in time and resources. Statistical expertise in the
design and analysis of microarray experiments is therefore in growing
demand. In an initial part of the Course, international experts will
lecture on data quality assessment, experimental design, data pre-processing
and normalization, model-based data analysis, differential expression
testing, and on statistical issues in multiple testing. In the second
part, emphasis will be given to statistical problems involved in the
integration of DNA sequence and gene expression data, with the aim of
uncovering important functional dependencies. The third part will cover
methods for representing complex multivariate distributions in the form
of networks, or graphs, with an underlying probabilistic interpretation
in terms of conditional independence. Emphasis will be given to applications
of these methods in the investigation of complex genetic systems and
of causal associations between gene expression and disease. The fifth
– and last – day will cover advanced applications of the
methods. The Course is addressed to a non necessarily statistical audience.
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