Weighted Network Analysis: Applications in Genomics and Systems Biology

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Springer Science & Business Media, 30.04.2011 - 421 Seiten
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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.
 

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Inhalt

Networks and Fundamental Concepts
1
Approximately Factorizable Networks
35
Different Types of Network Concepts
45
Adjacency Functions and Their Topological Effects
77
Correlation and Gene CoExpression Networks
91
Geometric Interpretation of Correlation Networks Using the Singular Value Decomposition
123
Constructing Networks from Matrices
161
Clustering Procedures and Module Detection
179
Association Measures and Statistical Significance Measures
249
Structural Equation Models and Directed Networks
279
Integrated Weighted Correlation Network Analysis of Mouse Liver Gene Expression Data
321
Networks Based on Regression Models and Prediction Methods
353
Networks Between Categorical or Discretized Numeric Variables
373
Network Based on the Joint Probability Distribution of Random Variables
401
Index
413
Urheberrecht

Evaluating Whether a Module is Preserved in Another Network
207

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Über den Autor (2011)

Steve Horvath and James Steiner have over sixty years of Sales and Management experience. They have experienced and learned from some of the best business practices. They excel at everything from Advertising and Marketing to Recruiting and Training.

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