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Weighted Network Analysis: Applications in Genomics and Systems Biology Hardcover – May 4, 2011

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ISBN-13: 978-1441988188 ISBN-10: 1441988181 Edition: 2011th

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Editorial Reviews

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. 

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Product Details

  • Hardcover: 421 pages
  • Publisher: Springer; 2011 edition (May 4, 2011)
  • Language: English
  • ISBN-10: 1441988181
  • ISBN-13: 978-1441988188
  • Product Dimensions: 9.4 x 6.3 x 1.2 inches
  • Shipping Weight: 1.7 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,893,250 in Books (See Top 100 in Books)

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2 of 2 people found the following review helpful By pierre charbord on June 29, 2013
Format: Hardcover Verified Purchase
Seminal book explaining how correlation networks between genes can be obtained. A must for transcriptome analysis. Accessible to any scientist with minimal background in statistics and transcriptome analysis.
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Weighted Network Analysis: Applications in Genomics and Systems Biology
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