Modeling In Computational Biology And Biomedicine
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| Author | : Frédéric Cazals |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 333 |
| Release | : 2012-11-06 |
| Genre | : Mathematics |
| ISBN | : 364231208X |
Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience.
| 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 | : Andreas Deutsch |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 408 |
| Release | : 2007-07-16 |
| Genre | : Mathematics |
| ISBN | : |
This edited volume contains a selection of chapters that are an outgrowth of the - ropean Conference on Mathematical and Theoretical Biology (ECMTB05, Dresden, Germany, July 2005). The peer-reviewed contributions show that mathematical and computational approaches are absolutely essential for solving central problems in the life sciences, ranging from the organizational level of individual cells to the dynamics of whole populations. The contributions indicate that theoretical and mathematical biology is a diverse and interdisciplinary ?eld, ranging from experimental research linked to mathema- cal modeling to the development of more abstract mathematical frameworks in which observations about the real world can be interpreted, and with which new hypotheses for testing can be generated. Today, much attention is also paid to the development of ef?cient algorithms for complex computation and visualisation, notably in molecular biology and genetics. The ?eld of theoretical and mathematical biology and medicine has profound connections to many current problems of great relevance to society. The medical, industrial, and social interests in its development are in fact indisputable.
| Author | : Dirk Husmeier |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 511 |
| Release | : 2006-05-06 |
| Genre | : Computers |
| ISBN | : 1846281199 |
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.
| Author | : Alexander Anderson |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 346 |
| Release | : 2007-08-08 |
| Genre | : Mathematics |
| ISBN | : 376438123X |
Aimed at postgraduate students in a variety of biology-related disciplines, this volume presents a collection of mathematical and computational single-cell-based models and their application. The main sections cover four general model groupings: hybrid cellular automata, cellular potts, lattice-free cells, and viscoelastic cells. Each section is introduced by a discussion of the applicability of the particular modelling approach and its advantages and disadvantages, which will make the book suitable for students starting research in mathematical biology as well as scientists modelling multicellular processes.
| Author | : P. Michael Conn |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 756 |
| Release | : 2008 |
| Genre | : Medical |
| ISBN | : 1588299333 |
The collection of systems represented in Sourcebook of genomic programs, although this work is certainly well Models for Biomedical Research is an effort to re?ect the represented and indexed. diversity and utility of models that are used in biomedicine. Some models have been omitted due to page limitations That utility is based on the consideration that observations and we have encouraged the authors to use tables and made in particular organisms will provide insight into the ? gures to make comparisons of models so that observations workings of other, more complex, systems. Even the cell not available in primary publications can become useful to cycle in the simple yeast cell has similarities to that in the reader. humans and regulation with similar proteins occurs. We thank Richard Lansing and the staff at Humana for Some models have the advantage that the reproductive, guidance through the publication process. mitotic, development or aging cycles are rapid compared As this book was entering production, we learned of the with those in humans; others are utilized because individual loss of Tom Lanigan, Sr. Tom was a leader and innovator proteins may be studied in an advantageous way and that in scienti?c publishing and a good friend and colleague to have human homologs. Other organisms are facile to grow all in the exploratory enterprise. We dedicate this book to in laboratory settings or lend themselves to convenient analy- his memory. We will miss him greatly.
| Author | : Paola Lecca |
| Publisher | : Elsevier |
| Total Pages | : 411 |
| Release | : 2013-04-09 |
| Genre | : Mathematics |
| ISBN | : 1908818212 |
Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic approach to biochemical kinetics, the book goes onto discuss the specifics of stochastic simulation algorithms, modelling in systems biology and the structure of biochemical models. Later chapters cover reaction-diffusion systems, and provide an analysis of the Kinfer and BlenX software systems. The final chapter looks at simulation of ecodynamics and food web dynamics. Introduces mathematical concepts and formalisms of deterministic and stochastic modelling through clear and simple examples Presents recently developed discrete stochastic formalisms for modelling biological systems and processes Describes and applies stochastic simulation algorithms to implement a stochastic formulation of biochemical and biological kinetics
| Author | : C. A. Brebbia |
| Publisher | : WIT Press |
| Total Pages | : 353 |
| Release | : 2009 |
| Genre | : Technology & Engineering |
| ISBN | : 1845641833 |
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.
| Author | : Uri Wilensky |
| Publisher | : MIT Press |
| Total Pages | : 505 |
| Release | : 2015-04-03 |
| Genre | : Computers |
| ISBN | : 0262731894 |
A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.
| Author | : Vitaly Volpert |
| Publisher | : MDPI |
| Total Pages | : 224 |
| Release | : 2021-01-26 |
| Genre | : Mathematics |
| ISBN | : 3039434934 |
Mathematical modelling in biomedicine is a rapidly developing scientific discipline at the intersection of medicine, biology, mathematics, physics, and computer science. Its progress is stimulated by fundamental scientific questions and by the applications to public health. This book represents a collection of papers devoted to mathematical modelling of various physiological problems in normal and pathological conditions. It covers a broad range of topics including cardiovascular system and diseases, heart and brain modelling, tumor growth, viral infections, and immune response. Computational models of blood circulation are used to study the influence of heart arrhythmias on coronary blood flow and on operating modes for left-ventricle-assisted devices. Wave propagation in the cardiac tissue is investigated in order to show the influence of tissue heterogeneity and fibrosis. The models of tumor growth are used to determine optimal protocols of antiangiogenic and radiotherapy. The models of viral hepatitis kinetics are considered for the parameter identification, and the evolution of viral quasi-species is investigated. The book presents the state-of-the-art in mathematical modelling in biomedicine and opens new perspectives in this passionate field of research.
