Titlebook: Recent Advances in Biological Network Analysis; Comparative Network Byung-Jun Yoon,Xiaoning Qian Book 2021 Springer Nature Switzerland AG

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978-3-030-57175-7Springer Nature Switzerland AG 2021

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atest techniques in computational network biology, especiall.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 internation

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Global Alignment of PPI Networksaring different global PPI network alignment outputs. Finally, we provide a discussion of relatively less studied aspects of the problem that may suggest potential open problems in need of further research on the topic.

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Integrated Network-Based Computational Analysis for Drug Developmentons of biological phenomena ranging from the molecule level to the disease level. This chapter describes the CODA-based computational models and discusses their benefits and/or limitations of each approach to achieve their aims.

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Global Alignment of PPI Networksks within them. Functional orthology detection, protein function prediction or verification, detection of common orthologous pathways, and reconstruction of the evolutionary dynamics of various species are some of the notable application areas of the global PPI network alignment problem. We focus on

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Effective Random Walk Models for Comparative Network Analysist it helps transferring the prior knowledge across different biological networks. Since identifying the optimal biological network alignment is practically infeasible due to the computational complexity, a number of heuristic network alignment algorithms have been proposed. Among various heuristic a

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Computational Methods for Protein–Protein Interaction Network Alignment is critical to the understanding of biomechanism and evolution. Protein–protein interaction (PPI) data is important for understanding biological processes at the system level. Comparative analysis of PPI networks of various species may yield valuable information, such as conserved subnetwork motifs

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