Modeling and analysis of bio-molecular networks /

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Bibliographic Details
Author / Creator:Lü, Jinhu, author.
Imprint:Singapore : Springer, [2020]
Description:1 online resource
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12609914
Hidden Bibliographic Details
Other authors / contributors:Wang, Pei, author.
ISBN:9789811591440
981159144X
9811591431
9789811591433
Digital file characteristics:text file
PDF
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed February 11, 2021).
Summary: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.
Other form:Print version: 9789811591433
Standard no.:10.1007/978-981-15-9144-0