Biological networks in human health and disease / Romana Ishrat, editor.
2023
QH324.2 .B56 2023
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Title
Biological networks in human health and disease / Romana Ishrat, editor.
ISBN
9789819942428 (electronic bk.)
981994242X (electronic bk.)
9819942411
9789819942411
981994242X (electronic bk.)
9819942411
9789819942411
Published
Singapore : Springer, 2023.
Language
English
Description
1 online resource (160 pages) : illustrations (black and white, and color).
Item Number
10.1007/978-981-99-4242-8 doi
Call Number
QH324.2 .B56 2023
Dewey Decimal Classification
570.1/13
Summary
This book presents methods and tools of network biology and bioinformatics for understanding the disease dynamics and identification of drug targets. The initial section of chapters introduce the theoretical aspects followed by the different applications for construction and analysis of biological networks, methods for identifying crucial nodes in networks, and network dynamics. The book covers the latest advances in the network medicine, exploring the different types of biological networks, and their applications. It further reviews the role of R language in the network-based approaches that help in understanding biological systems and identifying biological functions. Towards the end, the book explores the recent developments and applications in machine learning and its potential for advancing network biology. Finally, the book elucidates a comprehensive yet a representative description of challenges associated with the understanding of disease dynamics using network biology. Given its scope, the book is intended for researchers and advanced postgraduate students of bioinformatics, computational biology, and medical sciences.
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Chapter 1. Graph Theory in the Biological Networks
Chapter 2. Biological Networks Analysis
Chapter 3. Network Analysis based software packages, tools, and web servers to accelerate bioinformatics research
Chapter 4. Networks Analytics of Heterogeneous Big Data
Chapter 5. Network Medicine: Methods and Applications
Chapter 6. Role of R in Biological Network Analysis
Chapter 7. Machine Learning in Biological Networks.
Chapter 2. Biological Networks Analysis
Chapter 3. Network Analysis based software packages, tools, and web servers to accelerate bioinformatics research
Chapter 4. Networks Analytics of Heterogeneous Big Data
Chapter 5. Network Medicine: Methods and Applications
Chapter 6. Role of R in Biological Network Analysis
Chapter 7. Machine Learning in Biological Networks.