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portada Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-Based Precision Medicine
Type
Physical Book
Publisher
Language
Inglés
Pages
312
Format
Paperback
Dimensions
23.4 x 15.6 x 1.7 cm
Weight
0.45 kg.
ISBN13
9783030565121
Edition No.
0002

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

Vodovotz, Yoram ; An, Gary (Author) · Springer · Paperback

Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-Based Precision Medicine - Vodovotz, Yoram ; An, Gary

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

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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