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Medical Biostatistics for Complex Diseases

Medical Biostatistics for Complex Diseases

Frank Emmert-Streib (Editor), Matthias Dehmer (Editor)

ISBN: 978-3-527-63034-9

Mar 2010

412 pages

Select type: E-Book

$168.99

Description

A collection of highly valuable statistical and computational approaches designed for developing powerful methods to analyze large-scale high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the major health challenges in industrialized countries. They are characterized by the systems properties of gene networks and their interrelations, instead of individual genes, whose malfunctioning manifests in pathological phenotypes, thus making the analysis of the resulting large data sets particularly challenging. This is why novel approaches are needed to tackle this problem efficiently on a systems level. Written by computational biologists and biostatisticians, this book is an invaluable resource for a large number of researchers working on basic but also applied aspects of biomedical data analysis emphasizing the pathway level.
Preface (Emmert-Streib and Dehmer)
GENERAL BIOLOGICAL AND STATISTICAL BASICS
The biology of MYC in health and disease: a high altitude view (Turner, Bird and Refaeli)
Cancer Stem Cells -
Finding and Hitting the Roots of Cancer (Buss and Ho)
Multiple Testing Methods (Farcomeni)
STATISTICAL AND COMPUTATIONAL ANALYSIS METHODS
Making Mountains Out of Molehills: Moving from Single Gene to Pathway Based Models of Colon Cancer Progression (Edelman, Garman, Potti, Mukherjee)
Gene-Set Expression Analysis: Challenges and Tools (Oron)
Hotelling's T-2 multivariate profiling for detecting differential expression in microarrays (Lu, Liu, Deng)
Interpreting differential coexpression of gene sets (Ju Han Kim, Sung Bum Cho, Jihun Kim)
Multivariate analysis of microarray data: Application of MANOVA (Hwang and Park)
Testing Significance of a Class of Genes (Chen and Tsai)
Differential dependency network analysis to identify topological changes in biological networks (Zhang, Li, Clarke, Hilakivi-Clarke and Wang)
An Introduction to Time-Varying Connectivity Estimation for Gene Regulatory Networks (Fujita, Sato, Almeida Demasi, Miyano, Cleide Sogayar, and Ferreira)
A systems biology approach to construct a cancer-perturbed protein-protein interaction network for apoptosis by means of microarray and database mining (Chu and Chen)
NN, title not confirmed (Fishel, Ruppin)
Kernel Classification Methods for Cancer Microarray Data (Kato and Fujibuchi)
Predicting Cancer Survival Using Expression Patterns (Reddy, Kronek, Brannon, Seiler, Ganesan, Rathmell, Bhanot)
Integration of microarray data sets (Kim and Rha)
Model Averaging For Biological Networks With Prior Information (Mukherjeea, Speed and Hill)