Weighted Network Analysis - Applications in Genomics and Systems Biology

High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes.

List of contents

Preface.- Networks and fundamental concepts.- Approximately factorizable networks.- Different type of network concepts.- Adjacency functions and their topological effects.- Correlation and gene co-expression networks.- Geometric interpretation of correlation networks using the singular value decomposition.- Constructing networks from matrices.- Clustering Procedures and module detection.- Evaluating whether a module is preserved in another network.- Association and statistical significance measures.- Structural equation models and directed networks.- Integrated weighted correlation network analysis of mouse liver gene expression data.- Networks based on regression models and prediction methods.- Networks between categorical or discretized numeric variables.- Networks based on the joint probability distribution of random variables.- Index.

Summary

High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes.

Product details

• Authors: Steve Horvath
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2011
• EAN: 9781493900220
• ISBN: 978-1-4939-0022-0
• No. of pages: 421
• Dimensions: 157 mm x 234 mm x 26 mm
• Weight: 682 g
• Illustrations: XXIII, 421 p.
• Subjects: Natural sciences, medicine, IT, technology > Biology > Miscellaneous; B, molecular biology, bioinformatics, Biology, life sciences, Human Genetics, Biomedical and Life Sciences, Medical Genetics, Systems Biology, Information technology: general issues, Computational and Systems Biology, Computational biology, Computer Appl. in Life Sciences, newjc