Weighted Network Analysis

Applications in Genomics and Systems Biology
2011
ISBN: 978-1-4939-0022-0
Verlag: Springer

Buch, Englisch, 421 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 674 g

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Horvath, Steve

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Vorklinische Medizin: Grundlagenfächer Humangenetik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik

Inhaltsverzeichnis

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.