Systems Biomedicine is a field in perpetual development. By definition a translational discipline, it emphasizes the role of quantitative systems approaches in biomedicine and aims to offer solutions to many emerging problems characterized by levels and types of complexity and uncertainty unmet before. Many factors, including technological and societal ones, need to be considered. In particular, new technologies are providing researchers with the data deluge whose management and exploitation requires a reinvention of cross-disciplinary team efforts. The advent of “omics” and high-content imaging are examples of advances de facto establishing the necessity of systems approaches. Hypothesis-driven models and in silico validation tools in support to all the varieties of experimental applications call for a profound revision. The focus on phases like mining and assimilating the data has substantially increased so to allow for interpretable knowledge to be inferred. Notably, to be able to tackle the newly generated data dimensionality, heterogeneity and complexity, model-free and data-driven intensive applications are increasingly shaping the computational pipelines and architectures that quant specialists set aside of the high-throughput genomics, transcriptomics, proteomics platforms. As for the societal aspects, in many advanced societies health care needs now more than in the past to address the problem of managing ageing populations and their complex morbidity patterns. In parallel, there is a growing research interest on the impact that cross-disciplinary clinical, epidemiological and quantitative modelling studies can have in relation to outcomes potentially affecting the quality of life of many people. Complex systems, including those characterizing biomedicine, are assessed in both their functionality and stability, and also relatively to the capacity of generating information from diversity, variation, and complexity. Due to the combined interactions and effects, such systems embed prediction power available for instance in both target identification or marker discovery, or more generally for conducting inference about patients’ pathological states, i.e. normal versus disease, diagnostic or prognostic analysis, and preventive assessment (e.g., risk evaluation). The ultimate goal, personalized medicine, will be achieved based on the confluence of the system’s predictive power to patient-specific profiling.

Systems biology is a critical emerging field that quantifies and annotates the complexity of biological systems in order to construct algorithmic models to predict outcomes from component input. Applications in medicine are revolutionizing our understanding of biological processes and systems. Systems Biomedicine is organized around foundations, computational modeling, network biology, and integrative biology, with the extension of examples from human biology and pharmacology, to focus on the applications of systems approaches to medical problems. An integrative approach to the underlying genomic, proteomic, and computational biology principles provides researchers with guidance in the use of qualitative systems and hypothesis generators. To reflect the highly interdisciplinary nature of the field, careful detail has been extended to ensure explanations of complex mathematical and biological principles are clear with minimum technical jargon. - Organized to reflect the important distinguishing characteristics of systems strategies in experimental biology and medicine - Provides precise and comprehensive measurement tools for constructing a model of the system and tools for defining complexity as an experimental dependent variable - Includes a thorough discussion of the applications of quantitative principles to biomedical problems

Complex Systems Science in Biomedicine Thomas S. Deisboeck and J. Yasha Kresh Complex Systems Science in Biomedicine covers the emerging field of systems science involving the application of physics, mathematics, engineering and computational methods and techniques to the study of biomedicine including nonlinear dynamics at the molecular, cellular, multi-cellular tissue, and organismic level. With all chapters helmed by leading scientists in the field, Complex Systems Science in Biomedicine's goal is to offer its audience a timely compendium of the ongoing research directed to the understanding of biological processes as whole systems instead of as isolated component parts. In Parts I & II, Complex Systems Science in Biomedicine provides a general systems thinking perspective and presents some of the fundamental theoretical underpinnings of this rapidly emerging field. Part III then follows with a multi-scaled approach, spanning from the molecular to macroscopic level, exemplified by studying such diverse areas as molecular networks and developmental processes, the immune and nervous systems, the heart, cancer and multi-organ failure. The volume concludes with Part IV that addresses methods and techniques driven in design and development by this new understanding of biomedical science. Key Topics Include: • Historic Perspectives of General Systems Thinking • Fundamental Methods and Techniques for Studying Complex Dynamical Systems • Applications from Molecular Networks to Disease Processes • Enabling Technologies for Exploration of Systems in the Life Sciences Complex Systems Science in Biomedicine is essential reading for experimental, theoretical, and interdisciplinary scientists working in the biomedical research field interested in a comprehensive overview of this rapidly emerging field. About the Editors: Thomas S. Deisboeck is currently Assistant Professor of Radiology at Massachusetts General Hospital and Harvard Medical School in Boston. An expert in interdisciplinary cancer modeling, Dr. Deisboeck is Director of the Complex Biosystems Modeling Laboratory which is part of the Harvard-MIT Martinos Center for Biomedical Imaging. J. Yasha Kresh is currently Professor of Cardiothoracic Surgery and Research Director, Professor of Medicine and Director of Cardiovascular Biophysics at the Drexel University College of Medicine. An expert in dynamical systems, he holds appointments in the School of Biomedical Engineering and Health Systems, Dept. of Mechanical Engineering and Molecular Pathobiology Program. Prof. Kresh is Fellow of the American College of Cardiology, American Heart Association, Biomedical Engineering Society, American Institute for Medical and Biological Engineering.

Comprehensively presents the foundations and leading application research in medical informatics/biomedicine. The concepts and techniques are illustrated with detailed case studies. Authors are widely recognized professors and researchers in Schools of Medicine and Information Systems from the University of Arizona, University of Washington, Columbia University, and Oregon Health & Science University. Related Springer title, Shortliffe: Medical Informatics, has sold over 8000 copies The title will be positioned at the upper division and graduate level Medical Informatics course and a reference work for practitioners in the field.

While the use of database technology is ubiquitous throughout IT (and health IT in particular), it is not generally appreciated that, as a database increases in scope, certain designs are far superior to others. In biomedical domains, new knowledge is being generated continually, and the databases that must support areas such as clinical care and research must also be able to evolve while requiring minimal or no logical / physical redesign. Appropriately designed metadata, and software designed to utilize it effectively, can provide significant insulation against change. Many of the larger EMR or clinical research database vendors have realized this, but their designs are proprietary and not described in the literature. Consequently, numerous misconceptions abound among individuals who have not had to work with large-scale biomedical systems, and graduates of a health or bioinformatics program may find that they need to unlearn what they were taught in database and software design classes in order to work productively with such systems. A working knowledge of such systems is also important for individuals who are not primarily software developers, such as health informaticians, medical information officers and data analysts. This book is, in a sense, intended to prepare all of the above individuals for the real world.

Examining medical pluralism in the United States from the Revolutionary War period through the end of the twentieth century, Hans Baer brings together in one convenient reference a vast array of information on healing systems as diverse as Christian Science, osteopathy, acupuncture, Santeria, southern Appalachian herbalism, evangelical faith healing, and Navajo healing. In a country where the dominant paradigm of biomedicine (medical schools, research hospitals, clinics staffed by M.D.s and R.N.s) has been long established and supported by laws and regulations, the continuing appeal of other medical systems and subsystems bears careful consideration. Distinctions of class, Baer emphasizes, as well as differences in race, ethnicity, and gender, are fundamental to the diversity of beliefs, techniques, and social organizations represented in the phenomenon of medical pluralism. Baer traces the simultaneous emergence in the nineteenth century of formalized biomedicine and of homeopathy, botanic medicine, hydropathy, Christian Science, osteopathy, and chiropractic. He examines present-day osteopathic medicine as a system parallel to biomedicine with an emphasis on primary care; chiropractic, naturopathy, and acupuncture as professionalized heterodox medical systems; homeopathy, herbalism, bodywork, and lay midwifery in the context of the holistic health movement; Anglo-American religious healing; and folk medical systems, particularly among racial and ethnic minorities. In closing he focuses on the persistence of folk medical systems among working-class Americans and considers the growing interest of biomedical physicians, pharmaceutical and healthcare corporations, and government in the holistic health movement

During the 1990s, an unprecedented number of Americans turned to complementary and alternative medicine (CAM), an umbrella term encompassing chiropractic, energy healing, herbal medicine, homeopathy, meditation, naturopathy, and traditional Chinese medicine. By 1997, nearly half the US population was seeking CAM, spending at least $27 billion out of pocket. Bounding Biomedicine centers on this boundary-changing era, looking at how consumer demand shook the health care hierarchy. Drawing on scholarship in rhetoric and science and technology studies, the book examines how the medical profession scrambled to maintain its position of privilege and prestige, even as its foothold appeared to be crumbling. Colleen Derkatch analyzes CAM-themed medical journals and related discourse to illustrate how members of the medical establishment applied Western standards of evaluation and peer review to test health practices that did not fit easily (or at all) within standard frameworks of medical research. And she shows that, despite many practitioners’ efforts to eliminate the boundaries between “regular” and “alternative,” this research on CAM and the forms of communication that surrounded it ultimately ended up creating an even greater division between what counts as safe, effective health care and what does not. At a time when debates over treatment choices have flared up again, Bounding Biomedicine gives us a possible blueprint for understanding how the medical establishment will react to this new era of therapeutic change.