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Biological networks in human health ...

Ishrat, Romana.

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Biological networks in human health and disease

Record Type:	Electronic resources : Monograph/item
Title/Author:	Biological networks in human health and disease/ edited by Romana Ishrat.
other author:	Ishrat, Romana.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	x, 125 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Systems biology. -
Online resource:	https://doi.org/10.1007/978-981-99-4242-8
ISBN:	9789819942428

Biological networks in human health and disease
Biological networks in human health and disease[electronic resource] /edited by Romana Ishrat. - Singapore :Springer Nature Singapore :2023. - x, 125 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9789819942428

Standard No.: 10.1007/978-981-99-4242-8doiSubjects--Topical Terms:

905904
Systems biology.

LC Class. No.: QH324.2 / .B56 2023

Dewey Class. No.: 570.113

Biological networks in human health and disease
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245 0 0 $a Biological networks in human health and disease $h [electronic resource] / $c edited by Romana Ishrat.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a x, 125 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Systems biology. $3 905904
650 0 $a Diseases $x Mathematical models. $3 3667191
650 0 $a Chemotherapy. $3 728559
650 0 $a Artificial intelligence $x Medical applications. $3 900591
650 1 4 $a Computational and Systems Biology. $3 3531279
650 2 4 $a Bioinformatics. $3 553671
650 2 4 $a Diseases. $3 618693
700 1 $a Ishrat, Romana. $3 3667190
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-99-4242-8
950 $a Biomedical and Life Sciences (SpringerNature-11642)