Modeling and Analysis of Bio-molecular Networks [electronic resource] /

1 Introduction and Preliminaries -- 2 Reconstruction of Bio-molecular Networks -- 3 Modeling and Analysis of Simple Genetic Circuits -- 4 Modeling and Analysis of Coupled Bio-molecular Circuits -- 5 Modeling and Analysis of Large-scale Networks -- 6 Evolutionary Mechanisms of Network Motifs in PPI Networks -- 7 Identifying Important Nodes in Bio-molecular Networks -- 8 Statistical Analysis of Functional Genes in Human PPI Networks -- 9 Data-driven Statistical Approaches for Omics Data Analysis.

This book addresses a number of questions from the perspective of complex systems: How can we quantitatively understand the life phenomena? How can we model life systems as complex bio-molecular networks? Are there any methods to clarify the relationships among the structures, dynamics and functions of bio-molecular networks? How can we statistically analyse large-scale bio-molecular networks? Focusing on the modeling and analysis of bio-molecular networks, the book presents various sophisticated mathematical and statistical approaches. The life system can be described using various levels of bio-molecular networks, including gene regulatory networks, and protein-protein interaction networks. It first provides an overview of approaches to reconstruct various bio-molecular networks, and then discusses the modeling and dynamical analysis of simple genetic circuits, coupled genetic circuits, middle-sized and large-scale biological networks, clarifying the relationships between the structures, dynamics and functions of the networks covered. In the context of large-scale bio-molecular networks, it introduces a number of statistical methods for exploring important bioinformatics applications, including the identification of significant bio-molecules for network medicine and genetic engineering. Lastly, the book describes various state-of-art statistical methods for analysing omics data generated by high-throughput sequencing. This book is a valuable resource for readers interested in applying systems biology, dynamical systems or complex networks to explore the truth of nature.