Springer 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. 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. About the Author Dr. Yoram Vodovotz is currently a Professor of Surgery, Immunology, Computational and Systems Biology, Bioengineering, Clinical and Translational Science, and Communication Science and Disorders at the University of Pittsburgh School of Medicine. His research focus is the systems biology of inflammation. He is the Director of the Center for Inflammation and Regeneration Modeling at the McGowan Institute for Regenerative Medicine, a co-founder and past President of the Society for Complex Acute Illness, and a co-founder of Immunetrics, Inc., a Pittsburgh-based company that is commercializing this mathematical modeling work. He has published over 300 manuscripts, including three books. Dr. Gary An is a Professor of Surgery and Vice-Chairman for Surgical Research in the Department of Surgery at the University of Vermont Larner College of Medicine. He is a founding member of the Society of Complexity in Acute Illness and past president of the Swarm Development Group, one of the original organizations promoting the use of agent-based modeling for scientific investigation. In addition to being