Modeling and Analysis of Bio-molecular Networks

Modeling and Analysis of Bio-molecular Networks
Author :
Publisher : Springer Nature
Total Pages : 464
Release :
ISBN-10 : 9789811591440
ISBN-13 : 981159144X
Rating : 4/5 (44X Downloads)

Book Synopsis Modeling and Analysis of Bio-molecular Networks by : Jinhu Lü

Download or read book Modeling and Analysis of Bio-molecular Networks written by Jinhu Lü and published by Springer Nature. This book was released on 2020-12-06 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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