Become a Readings Member to make your shopping experience even easier. Sign in or sign up for free!

Become a Readings Member. Sign in or sign up for free!

Hello Readings Member! Go to the member centre to view your orders, change your details, or view your lists, or sign out.

Hello Readings Member! Go to the member centre or sign out.

Bayesian Inference for Gene Expression and Proteomics
Hardback

Bayesian Inference for Gene Expression and Proteomics

$284.99
Sign in or become a Readings Member to add this title to your wishlist.

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.

Read More
In Shop
Out of stock
Shipping & Delivery

$9.00 standard shipping within Australia
FREE standard shipping within Australia for orders over $100.00
Express & International shipping calculated at checkout

MORE INFO
Format
Hardback
Publisher
Cambridge University Press
Country
United Kingdom
Date
24 July 2006
Pages
456
ISBN
9780521860925

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.

Read More
Format
Hardback
Publisher
Cambridge University Press
Country
United Kingdom
Date
24 July 2006
Pages
456
ISBN
9780521860925