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Bayesian Inference for Gene Expression and Proteomics (Paperback)
Loot Price: R1,415
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Bayesian Inference for Gene Expression and Proteomics (Paperback)
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The interdisciplinary nature of bioinformatics presents a research
challenge in integrating concepts, methods, software and
multiplatform data. Although there have been rapid developments in
new technology and an inundation of statistical methods for
addressing other types of high-throughput data, such as proteomic
profiles that arise from mass spectrometry experiments. This book
discusses the development and application of Bayesian methods in
the analysis of high-throughput bioinformatics data that arise from
medical, in particular, cancer research, as well as molecular and
structural biology. The Bayesian approach has the advantage that
evidence can be easily and flexibly incorporated into statistical
methods. A basic overview of the biological and technical
principles behind multi-platform high-throughput experimentation is
followed by expert reviews of Bayesian methodology, tools and
software for single group inference, group comparisons,
classification and clustering, motif discovery and regulatory
networks, and Bayesian networks and gene interactions.
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