Overview
- Includes cutting-edge methods and protocols
- Provides step-by-step detail essential for reproducible results
- Contains key notes and implementation advice from the experts
Part of the book series: Methods in Molecular Biology (MIMB, volume 2634)
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About this book
This volume focuses on the computational modeling of cell signaling networks and the application of these models and model-based analysis to systems and personalized medicine. Chapters guide readers through various modeling approaches for signaling networks, new methods and techniques that facilitate model development and analysis, and new applications of signaling network modeling towards systems and personalized treatment of cancer. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.
Authoritative and cutting-edge, Computational Modeling of Signaling Networks aims to benefit a wide spectrum of readers including researchers from the biological as well as computational systems biology communities.
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Keywords
Table of contents (17 protocols)
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Advances in Computational Modelling of Signalling Networks
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Advances in Integrative Analysis of Signalling Networks
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Application of Integrative Modelling and Analysis of Signalling Networks in Diseases
Editors and Affiliations
Bibliographic Information
Book Title: Computational Modeling of Signaling Networks
Editors: Lan K. Nguyen
Series Title: Methods in Molecular Biology
DOI: https://doi.org/10.1007/978-1-0716-3008-2
Publisher: Humana New York, NY
eBook Packages: Springer Protocols
Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2023
Hardcover ISBN: 978-1-0716-3007-5Published: 20 April 2023
Softcover ISBN: 978-1-0716-3010-5Published: 20 April 2023
eBook ISBN: 978-1-0716-3008-2Published: 19 April 2023
Series ISSN: 1064-3745
Series E-ISSN: 1940-6029
Edition Number: 1
Number of Pages: XI, 386
Number of Illustrations: 7 b/w illustrations, 118 illustrations in colour
Topics: Bioinformatics, Cancer Research, Cell Biology