Bayesian Inference for Gene Expression and Proteomics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Muller, Peter (EDT)/ Vannucci, Marina (EDT) 作者

Cambridge Univ Pr

译者

2006-7 出版日期

437 页数

$ 123.17 价格

HRD

丛书系列

9780521860925 图书编码

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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.

Bayesian Inference for Gene Expression and Proteomics 在线电子书下载 mobi epub pdf txt 在线电子书下载

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