Chapter 1: Global Alignment of PPI Networks -- Chapter 2: Integrated Network-Based Computational Analysis for Drug Development -- Chapter 3: Effective Random Walk Models for Comparative Network Analysis -- Chapter 4: Computational Methods for Protein-Protein Interaction Network Alignment -- Chapter 5: Network Propagation for the Analysis of Multi_Omics Data -- Chapter 6: Motifs in Biological Networks -- Chapter 7: Bio Fabric Visualization of Network Alignments -- Chapter 8: Module Identification of Biological Networks via Graph Partition -- Chapter 9: Network Module Detection to Decipher the Heterogeneity of Cancer Mutations.

This book reviews recent advances in the emerging field of computational network biology with special emphasis on comparative network analysis and network module detection. The chapters in this volume are contributed by leading international researchers in computational network biology and offer in-depth insight on the latest techniques in network alignment, network clustering, and network module detection. Chapters discuss the advantages of the respective techniques and present the current challenges and open problems in the field. Recent Advances in Biological Network Analysis: Comparative Network Analysis and Network Module Detection will serve as a great resource for graduate students, academics, and researchers who are currently working in areas relevant to computational network biology or wish to learn more about the field. Data scientists whose work involves the analysis of graphs, networks, and other types of data with topological structure or relations can also benefit from the book's insights. .