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Books > Medicine > Clinical & internal medicine > Diseases & disorders > Oncology
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Statistical Diagnostics for Cancer - Analyzing High-Dimensional Data (Hardcover)
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Statistical Diagnostics for Cancer - Analyzing High-Dimensional Data (Hardcover)
Series: Quantitative and Network Biology (VCH)
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This ready reference discusses different methods for statistically
analyzing and validating data created with high-throughput methods.
As opposed to other titles, this book focusses on systems
approaches, meaning that no single gene or protein forms the basis
of the analysis but rather a more or less complex biological
network. From a methodological point of view, the well balanced
contributions describe a variety of modern supervised and
unsupervised statistical methods applied to various large-scale
datasets from genomics and genetics experiments. Furthermore, since
the availability of sufficient computer power in recent years has
shifted attention from parametric to nonparametric methods, the
methods presented here make use of such computer-intensive
approaches as Bootstrap, Markov Chain Monte Carlo or general
resampling methods. Finally, due to the large amount of information
available in public databases, a chapter on Bayesian methods is
included, which also provides a systematic means to integrate this
information. A welcome guide for mathematicians and the medical and
basic research communities.
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