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Computational Modeling of Signaling Networks
Computational Modeling of Signaling Networks
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- More about Computational Modeling of Signaling Networks
This volume focuses on the computational modeling of cell signaling networks and their application to systems and personalized medicine. It includes chapters on modeling approaches, methods, and applications, written in the format of the highly successful Methods in Molecular Biology series.
Format: Hardback
Length: 386 pages
Publication date: 20 April 2023
Publisher: Springer-Verlag New York Inc.
This comprehensive volume delves into the intricate realm of computational modeling of cell signaling networks, showcasing its profound application in systems and personalized medicine. Spanning multiple chapters, it serves as a valuable guide for readers seeking to comprehend and harness the power of these models for understanding complex biological systems. The chapters meticulously explore diverse modeling approaches, introducing novel methods and techniques that expedite the development and analysis of signaling network models. Furthermore, they shed light on innovative applications of signaling network modeling in the realm of systems and personalized cancer treatment. Written in the esteemed format of the highly successful Methods in Molecular Biology series, each chapter encompasses an insightful introduction, a comprehensive list of necessary materials and methods, practical tips on troubleshooting and potential pitfalls, and meticulously detailed, readily reproducible protocols. Authored by esteemed experts in the field, this authoritative and cutting-edge text is poised to cater to a diverse readership, including researchers from both the biological and computational systems biology communities. By unraveling the complexities of cell signaling networks, Computational Modeling of Signaling Networks empowers readers to make groundbreaking discoveries, drive innovation, and advance personalized healthcare to new heights.
Weight: 947g
Dimension: 254 x 178 (mm)
ISBN-13: 9781071630075
Edition number: 1st ed. 2023
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