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Featuring contributions from the Sixth International Conference on Modelling in Medicine and Biology, this volume covers a broad spectrum of topics including the application of computers to simulate biomedical phenomena. It will be of interest both to medical and physical scientists and engineers and to professionals working in medical enterprises actively involved in this field.Areas highlighted include: Simulation of Physiological Processes; Computational Fluid Dynamics in Biomedicine; Orthopaedics and Bone Mechanics; Simulations in Surgery; Design and Simulation of Artificial Organs; Computers and Expert Systems in Medicine; Advanced Technology in Dentistry; Gait and Motion Analysis; Cardiovascular System; Virtual Reality in Medicine; Biomechanics; and Neural Systems.
Featuring contributions from the eighth International Conference on Modelling in Medicine and Biology, this volume covers a broad spectrum of topics including the application of computers to simulate biomedical phenomena. It will be of interest to medical and physical scientists and engineers.
Projections for advances in medical and biological technology will transform medical care and treatment. This is in great part due to the results of interaction and collaborations between the medical sciences and engineering. These advances will result in substantial progressions in health care and in the quality of life of the population.Computer models in particular have been increasingly successful in simulating biological phenomena. These are lending support to many applications, including amongst others cardiovascular systems, the study of orthopaedics and biomechanics, electrical simulation. Another important contribution, due to the wide availability of computational facilities and the development of better numerical algorithms, is the ability to acquire analyses, manage and visualise massive amounts of data. Containing papers presented at the Seventh International Conference on Modelling in Medicine and Biology, this book covers a broad range of topics which will be of particular interest to medical and physical scientists and engineers interested in the latest developments in simulations in medicine. It will also be relevant to professionals working in medical enterprises which are actively involved in this field. Topics include: Cardiovascular Systems; Simulations in Surgery; Biomechanics; Advanced Technology in Dentistry; Simulation of Physiological Processes; Neural Systems; Computational Fluid Dynamics in Biomedicine; Orthopaedics and Bone Mechanics; Data Acquisition and Analysis; Virtual Reality in Medicine; Expert Systems in Medicine; Design and Simulation of Artificial Organs.
Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community, it shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in this book are still important and informative. Audience: the book does not assume too much background knowledge--essentially some calculus and high-school algebra. It was originally written with third- and fourth-year undergraduate mathematical-biology majors in mind; however, it was picked up by beginning graduate students as well as researchers in math (and some in biology) who wanted to learn about this field.
Regenerative Biology and Medicine, Second Edition — Winner of a 2013 Highly Commended BMA Medical Book Award for Medicine — discusses the fundamentals of regenerative biology and medicine. It provides a comprehensive overview, which integrates old and new data into an ever-clearer global picture. The book is organized into three parts. Part I discusses the mechanisms and the basic biology of regeneration, while Part II deals with the strategies of regenerative medicine developed for restoring tissue, organ, and appendage structures. Part III reflects on the achievements of regenerative biology and medicine; future challenges; bioethical issues that need to be addressed; and the most promising developments in regenerative medicine. The book is designed for multiple audiences: undergraduate students, graduate students, medical students and postdoctoral fellows, and research investigators interested in an overall synthesis of this field. It will also appeal to investigators from fields not directly related to regenerative biology and medicine, such as chemistry, informatics, computer science, mathematics, physics, and engineering. - Highly Commended 2013 BMA Medical Book Award for Medicine - Includes coverage of skin, hair, teeth, cornea, and central neural tissues - Provides description of regenetive medicine in digestive, respiratory, urogenital, musculoskeletal, and cardiovascular systems - Includes amphibians as powerful research models with discussion of appendage regeneration in amphibians and mammals
Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.
This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?
A mathematician who has taken the romantic decision to devote himself to biology will doubtlessly look upon cell kinetics as the most simple and natural field of application for his knowledge and skills. Indeed, the thesaurus he is to master is not so complicated as, say, in molecular biology, the structural elements of the system, i. e. ceils, have been segregated by Nature itself, simple considerations of balance may be used for deducing basic equations, and numerous analogies in other areas of science also superficial add to one"s confidence. Generally speaking, this number of impression is correct, as evidenced by the very great theoretical studies on population kinetics, unmatched in other branches of mathematical biology. This, however, does not mean that mathematical theory of cell systems has traversed in its development a pathway free of difficulties or errors. The seeming ease of formalizing the phenomena of cell kinetics not infrequently led to the appearance of mathematical models lacking in adequacy or effectiveness from the viewpoint of applications. As in any other domain of science, mathematical theory of cell systems has its own intrinsic logic of development which, however, depends in large measure on the progress in experimental biology. Thus, during a fairly long period running into decades activities in that sphere were centered on devising its own specific approaches necessitated by new objectives in the experimental in vivo and in vitro investigation of cell population kinetics in different tissues.
Depth Perception in Frogs and Toads provides a comprehensive exploration of the phenomenon of depth perception in frogs and toads, as seen from a neuro-computational point of view. Perhaps the most important feature of the book is the development and presentation of two neurally realizable depth perception algorithms that utilize both monocular and binocular depth cues in a cooperative fashion. One of these algorithms is specialized for computation of depth maps for navigation, and the other for the selection and localization of a single prey for prey catching. The book is also unique in that it thoroughly reviews the known neuroanatomical, neurophysiological and behavioral data, and then synthesizes, organizes and interprets that information to explain a complex sensory-motor task. The book will be of special interest to that segment of the neural computing community interested in understanding natural neurocomputational structures, particularly to those working in perception and sensory-motor coordination. It will also be of interest to neuroscientists interested in exploring the complex interactions between the neural substrates that underly perception and behavior.
One of my favorite quotes is from a letter of Charles Darwin (1887): "I have long discovered that geologists never read each other's works, and that the only object in writing a book is proof of earnestness, and that you do not form your opinions without undergoing labour of some kind. " It is not clear if this private opinion of Darwin was one that he held to be absolutely true, or was one of those opinions that, as with most of us, coincides with our "bad days," but is replaced with a more optimistic view on our "good days. " I hold the sense of the statement to be true in general, but not with regard to scientists never reading each other's work. Even if that were true however, the present essay. would still have been written as a proof of earnestness. This essay outlines my personal view of how nonlinear mathematics may be of value in formulating models outside the physical sciences. This perspective has developed over a number of years during which time I have repeatedly been amazed at how an "accepted" model would fail to faithfully characterize the full range of avail able data because of its implicit or explicit dependence on linear concepts. This essay is intended to demonstrate how linear ideas have come to dominate and therefore limit a scientist's ability to understand any given class of phenomena.