9783030565121-3030565122-Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine

Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine

ISBN-13: 9783030565121
ISBN-10: 3030565122
Edition: 2nd ed. 2021
Author: Yoram Vodovotz, Gary An
Publication date: 2021
Publisher: Springer
Format: Paperback 324 pages
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Book details

ISBN-13: 9783030565121
ISBN-10: 3030565122
Edition: 2nd ed. 2021
Author: Yoram Vodovotz, Gary An
Publication date: 2021
Publisher: Springer
Format: Paperback 324 pages

Summary

Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine (ISBN-13: 9783030565121 and ISBN-10: 3030565122), written by authors Yoram Vodovotz, Gary An, was published by Springer in 2021. With an overall rating of 4.5 stars, it's a notable title among other Anatomy (Biological Sciences, Bioinformatics, Immunology, Basic Medical Sciences) books. You can easily purchase or rent Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine (Paperback) from BooksRun, along with many other new and used Anatomy books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This second edition expands upon and updates the vital research covered in its predecessor, by presenting state-of-the-art multidisciplinary and systems-oriented approaches to complex diseases arising from and driven by the acute inflammatory response. The chapters in this volume provide an introduction to different types of computational modeling, and how these methods can be applied to specific inflammatory diseases, with a focus on providing readers a roadmap for integrating advanced mathematical and computational techniques with traditional experimental methods. In this second edition, we cover both well-established and emerging modeling methods, especially state-of-the-art machine learning approaches and the integration of data-driven and mechanistic modeling.
This volume introduces the concept of Model-based Precision Medicine as an alternative approach to the current view of Precision Medicine, based on leveraging mechanistic computational modeling to decrease cost while increasing the information value of the data being obtained.
By presenting the role of computational modeling as an integrated component of the research process, Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine offers a window into the recent past, the present, and the future of computationally-augmented biomedical research.
From the Back Cover
This second edition expands upon and updates the vital research covered in its predecessor, by presenting state-of-the-art multidisciplinary and systems-oriented approaches to complex diseases arising from and driven by the acute inflammatory response. The chapters in this volume provide an introduction to different types of computational modeling, and how these methods can be applied to specific inflammatory diseases, with a focus on providing readers a roadmap for integrating advanced mathematical and computational techniques with traditional experimental methods. In this second edition, we cover both well-established and emerging modeling methods, especially state-of-the-art machine learning approaches and the integration of data-driven and mechanistic modeling.
This volume introduces the concept of Model-based Precision Medicine as an alternative approach to the current view of Precision Medicine, based on leveraging mechanistic computational modeling to decrease cost while increasing the information value of the data being obtained.
By presenting the role of computational modeling as an integrated component of the research process, Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine offers a window into the recent past, the present, and the future of computationally-augmented biomedical research.

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