TY  - BOOK
AU  - Do,Kim-Anh
AU  - Müller,Peter
AU  - Vannucci,Marina
TI  - Bayesian inference for gene expression and proteomics
SN  - 9780511584589 (ebook)
AV  - QH450 .B39 2006
U1  - 572.8/6501519542 22
PY  - 2006///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Gene expression
KW  - Statistical methods
KW  - Proteomics
N1  - Title from publisher's bibliographic system (viewed on 05 Oct 2015)
N2  - 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
UR  - https://doi.org/10.1017/CBO9780511584589
ER  -