Weighted Network Analysis: Applications in Genomics and Systems Biology - Softcover

Horvath, Steve

Softcover

ISBN 10: 1493900226 ISBN 13: 9781493900220

Publisher: Springer, 2014

Synopsis

This book offers current methods, software and applications involved in weighted networks, reviewing data mining methods and analysis strategies and showing how to use them in practice. The self-contained presentation requires minimal knowledge of statistics.

About this title

From the Back Cover

This book presents state-of-the-art methods, software and applications surrounding weighted networks. Most methods and results also apply to unweighted networks. Although aspects of weighted network analysis relate to standard data mining methods, the intuitive network language and analysis framework transcend any particular analysis method. Weighted networks give rise to data reduction methods, clustering procedures, visualization methods, data exploratory methods, and intuitive approaches for integrating disparate data sets. Weighted networks have been used to analyze a variety of high dimensional genomic data sets including gene expression-, epigenetic-, methylation-, proteomics-, and fMRI- data. Chapters explore the fascinating topological structure of weighted networks and provide geometric interpretations of network methods. Powerful systems-level analysis methods result from combining network- with data mining methods. The book not only describes the WGCNA R package but also other software packages. Weighted gene co-expression network applications, real data sets, and exercises guide the reader on how to use these methods in practice, e.g. in systems-biologic or systems-genetic applications. The material is self-contained and only requires a minimum knowledge of statistics. The book is intended for students, faculty, and data analysts in many fields including bioinformatics, computational biology, statistics, computer science, biology, genetics, applied mathematics, physics, and social science. 

Edition details

• Publisher: Springer
• Publication date: 2014
• ISBN 10: 1493900226
• ISBN 13: 9781493900220
• Binding: Paperback
• Language: English
• Number of pages: 444