Dehmer M., Shi Y., Emmert-Streib F. (Eds.) Computational Network Analysis With R: Applications in Biology, Medicine and Chemistry

Wiley-VCH, 2017. — 355 p. — (Quantitative and Network Biology. Volume 7). — ISBN10: 3527339582.This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics.
With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping.
Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.Using the DiffCorr Package to Analyze and Visualize Differential Correlations in Biological Networks
Analytical Models and Methods for Anomaly Detection in Dynamic, Attributed Graphs
Bayesian Computational Algorithms for Social Network Analysis
Threshold Degradation in R Using iDEMO
Optimization of Stratified Sampling with the R Package SamplingStrata: Applications to Network Data
Exploring the Role of Small Molecules in Biological Systems Using Network Approaches
Performing Network Alignments with R
1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields
Cluster Analysis of Social Networks Using R
Inference and Analysis of Gene Regulatory Networks in R
Visualization of Biological Networks Using NetBioV