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Intl Conf "Pattern Recognition in Bioinformatics": submission deadline 5 June
Azioni sul documento
V International Course on Microarray Data Analysis
| Cosa | Meeting |
|---|---|
| Quando |
09/03/2009 09:00
al 13/03/2009 18:00 |
| Dove | Valencia, Spain |
| Aggiungi l'evento al calendario |
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DNA microarrays constitute, no doubt, a paradigm among post-genomic technologies, which are characterised for producing large amounts of data, whose analysis and interpretation is not trivial. Microarray technologies allows querying living systems in a completely new way, but at the same time present new challenges in the way hypotheses must be tested and our results ought to be analysed.
Since the first papers published in the latest
nineties the number of questions that have been
addressed through this technique have both
increased and diversified. Initial interest was
focused on genes co-expressing across sets of
experimental conditions, implying essentially
the use of clustering techniques. More recently,
however, the interest has switched to find genes
differentially expressed among distinct classes
of experiments, or correlated to diverse
parameters. There is also much interest in
robust methods for building predictors of
clinical outcomes. Also, CGH-arrays (Albertson
and Pinkel, 2003) are recently becoming an
alternative for studying the relationship
between chromosomal alterations affecting to
copy number (which are behind many diseases) and
gene expression. In addition, there is also a
clear demand for methods that allow automatic
transfer of biological information to the
results of microarray experiments and to
interpret them at the light of the biological
knowledge. Recently, new methods of analysis
have been proposed that directly address
hypothesis on modules of genes functionally
related that have demonstrated to be superior to
the classical one-gene-at-a-time approaches
(Mootha et al., 2003; Al-Shahrour et al., 2005,
2007). New high throughput sequencing methods
will increase the availability of transcriptomic
and genomic data in a different format but with
the same scientific questions behind.
This course covers the state-of-the-art in the
above mentioned topics, which are of major
relevance in today’s gene expression data
analysis. Through sessions of theory and
practical examples, the students will acquire
the experience necessary to address scientific
questions to gene expression array datasets and
solve them. Special attention will be devoted to
important (although not always took into
account) aspects in microarray data analysis,
such as multiple testing or functional
profiling. In addition, some theoretical lessons
on basic statistics will be included as part of
the programme. Finally, for the bravest and
those who want to go in more depth into analysis
possibilities, the last day a short course on
Bioconductor (Gentleman et al., 2004) will be taught.
The course is designed to be a mixture of
theoretical and practical sessions. The latter
will require some familiarity with the use of
web-based tools and knowledge of basics notions of statistics.
Practical sessions will be carried out using the
GEPAS (Herrero et al., 2003, 2004, Vaquerizas et
al., 2005; Montaner et al., 2006) environment,
an integrated web tool for microarray data
analysis, and the Babelomics suite (Al-Shahrour
et al., 2005b, 2006, 2007) for functional
profiling of genome-scale experiments, and the
Blast2GO suite (Conesa et al., 2005), a set of
tools for the high-throughput functional
annotation and analysis of uncharacterized sequences
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