Systems Biomedicine
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| Author | : Edison T. Liu |
| Publisher | : Academic Press |
| Total Pages | : 450 |
| Release | : 2009-09-17 |
| Genre | : Science |
| ISBN | : 0080919839 |
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
| Author | : Thomas Deisboeck |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 857 |
| Release | : 2007-06-13 |
| Genre | : Medical |
| ISBN | : 0387335323 |
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.
| Author | : Hans A. Baer |
| Publisher | : Univ of Wisconsin Press |
| Total Pages | : 238 |
| Release | : 2001 |
| Genre | : Alternative medicine |
| ISBN | : 9780299166946 |
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
| Author | : Pietro Lio |
| Publisher | : Frontiers E-books |
| Total Pages | : 114 |
| Release | : 2014-12-03 |
| Genre | : Genetics |
| ISBN | : 2889193748 |
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.
| Author | : Alberto D'Onofrio |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 398 |
| Release | : 2013-01-25 |
| Genre | : Mathematics |
| ISBN | : 8847025710 |
The future of oncology seems to lie in Molecular Medicine (MM). MM is a new science based on three pillars. Two of them are evident in its very name and are well known: medical science and molecular biology. However, there is a general unawareness that MM is firmly based on a third, and equally important, pillar: Systems Biomedicine. Currently, this term denotes multilevel, hierarchical models integrating key factors at the molecular, cellular, tissue, through phenotype levels, analyzed to reveal the global behavior of the biological process under consideration. It becomes increasingly evident that the tools to construct such complex models include, not only bioinformatics and modern applied statistics, as is unanimously agreed, but also other interdisciplinary fields of science, notably, Mathematical Oncology, Systems Biology and Theoretical Biophysics.
| Author | : Shailza Singh |
| Publisher | : Springer Nature |
| Total Pages | : 170 |
| Release | : 2022-08-10 |
| Genre | : Science |
| ISBN | : 9811919534 |
This book presents the applications of systems biology and synthetic biology in cancer medicine. It highlights the use of computational and mathematical models to decipher the complexity of cancer heterogeneity. The book emphasizes the modeling approaches for predicting behavior of cancer cells, tissues in context of drug response, and angiogenesis. It introduces cell-based therapies for the treatment of various cancers and reviews the role of neural networks for drug response prediction. Further, it examines the system biology approaches for the identification of medicinal plants in cancer drug discovery. It explores the opportunities for metabolic engineering in the realm of cancer research towards development of new cancer therapies based on metabolically derived targets. Lastly, it discusses the applications of data mining techniques in cancer research. This book is an excellent guide for oncologists and researchers who are involved in the latest cancer research.
| Author | : Michael Insana |
| Publisher | : Cambridge University Press |
| Total Pages | : 405 |
| Release | : 2021-06-17 |
| Genre | : Technology & Engineering |
| ISBN | : 1316832767 |
Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineering, computer science, medical physics, and anyone preparing for a career in biomedical sciences and engineering.
| Author | : Babak Sokouti |
| Publisher | : Elsevier |
| Total Pages | : 356 |
| Release | : 2024-11-05 |
| Genre | : Science |
| ISBN | : 0443223270 |
Systems Biology and In-Depth Applications for Unlocking Diseases: Principles, tools and Application to Disease provides the essence of systems biology approaches in a practical manner, illustrating the basic principles essential to develop and model in real life science applications. Methodologies covered show how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment. Sections provide an introduction and history of systems biology, discuss the tools and resources needed for structure and function of biological systems, and present evidence of systems biology in action. Examples include big data techniques, scale networks, mathematical model development, and much more. This is the perfect reference to provide the fundamental base of knowledge needed for systems biologists, professionals in systems medicine, computational biologists, and bioinformaticians. - Provides detailed and comprehensive coverage of the field of systems biology - Delivers instruction on how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment - Makes effective steps towards personalized medicine in the treatment of disease - Explains effective disease treatment strategies at early diagnosis stages
| Author | : Aleš Prokop |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 569 |
| Release | : 2013-08-28 |
| Genre | : Medical |
| ISBN | : 9400768036 |
Growth in the pharmaceutical market has slowed down – almost to a standstill. One reason is that governments and other payers are cutting costs in a faltering world economy. But a more fundamental problem is the failure of major companies to discover, develop and market new drugs. Major drugs losing patent protection or being withdrawn from the market are simply not being replaced by new therapies – the pharmaceutical market model is no longer functioning effectively and most pharmaceutical companies are failing to produce the innovation needed for success. This multi-authored new book looks at a vital strategy which can bring innovation to a market in need of new ideas and new products: Systems Biology (SB). Modeling is a significant task of systems biology. SB aims to develop and use efficient algorithms, data structures, visualization and communication tools to orchestrate the integration of large quantities of biological data with the goal of computer modeling. It involves the use of computer simulations of biological systems, such as the networks of metabolites comprise signal transduction pathways and gene regulatory networks to both analyze and visualize the complex connections of these cellular processes. SB involves a series of operational protocols used for performing research, namely a cycle composed of theoretical, analytic or computational modeling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.
| Author | : Asfar S Azmi |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 424 |
| Release | : 2012-09-29 |
| Genre | : Medical |
| ISBN | : 9400748183 |
Systems Biology in Cancer Research and Drug Discovery provides a unique collection of chapters, by world-class researchers, describing the use of integrated systems biology and network modeling in the cancer field where traditional tools have failed to deliver expected promise. This book touches four applications/aspects of systems biology (i) in understanding aberrant signaling in cancer (ii) in identifying biomarkers and prognostic markers especially focused on angiogenesis pathways (iii) in unwinding microRNAs complexity and (iv) in anticancer drug discovery and in clinical trial design. This book reviews the state-of-the-art knowledge and touches upon cutting edge newer and improved applications especially in the area of network modeling. It is aimed at an audience ranging from students, academics, basic researcher and clinicians in cancer research. This book is expected to benefit the field of translational cancer medicine by bridging the gap between basic researchers, computational biologists and clinicians who have one ultimate goal and that is to defeat cancer.
