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Mathematical Methods In Immunology
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Book Synopsis Mathematical Methods in Immunology by : Jerome Kenneth Percus
Download or read book Mathematical Methods in Immunology written by Jerome Kenneth Percus and published by American Mathematical Soc.. This book was released on 2012 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any organism, to survive, must use a variety of defense mechanisms. A relatively recent evolutionary development is that of the adaptive immune system, carried to a quite sophisticated level by mammals. The complexity of this system calls for its encapsulation by mathematical models, and this book aims at the associated description and analysis. In the process, it introduces tools that should be in the armory of any current or aspiring applied mathematician, in the context of, arguably, the most effective system nature has devised to protect an organism from its manifold invisible enemies.
Book Synopsis Mathematical, Computational and Experimental T Cell Immunology by : Carmen Molina-París
Download or read book Mathematical, Computational and Experimental T Cell Immunology written by Carmen Molina-París and published by Springer Nature. This book was released on 2021-01-04 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical, statistical, and computational methods enable multi-disciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. This volume collects a representative sample of studies in T cell immunology that illustrate the benefits of modelling-experimental collaborations and which have proven valuable or even ground-breaking. Studies include thymic selection, T cell repertoire diversity, T cell homeostasis in health and disease, T cell-mediated immune responses, T cell memory, T cell signalling and analysis of flow cytometry data sets. Contributing authors are leading scientists in the area of experimental, computational, and mathematical immunology. Each chapter includes state-of-the-art and pedagogical content, making this book accessible to readers with limited experience in T cell immunology and/or mathematical and computational modelling.
Book Synopsis A Course in Mathematical Biology by : Gerda de Vries
Download or read book A Course in Mathematical Biology written by Gerda de Vries and published by SIAM. This book was released on 2006-07-01 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the only book that teaches all aspects of modern mathematical modeling and that is specifically designed to introduce undergraduate students to problem solving in the context of biology. Included is an integrated package of theoretical modeling and analysis tools, computational modeling techniques, and parameter estimation and model validation methods, with a focus on integrating analytical and computational tools in the modeling of biological processes. Divided into three parts, it covers basic analytical modeling techniques; introduces computational tools used in the modeling of biological problems; and includes various problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, including many exercises related to biological questions. In addition, 25 open-ended research projects are provided, suitable for students. An accompanying Web site contains solutions and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MATLAB?.
Book Synopsis New Approach Methods in Immunology by : Jeffrey John Bajramovic
Download or read book New Approach Methods in Immunology written by Jeffrey John Bajramovic and published by Frontiers Media SA. This book was released on 2024-09-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently, the assessment of functional immunological relevance is mainly done in animal models. Motivation to work on non-animal methods, or new approach methods (NAM), stems from economical and ethical considerations, and is supported by public pressure. Importantly, the translational gap between results obtained in animal studies and clinical trials in humans (the ‘valley of death’), combined with the reproducibility crisis in science, also provide strong scientific arguments to work on novel, robust, human-based methodology. The field of immunology confronts NAM scientists with specific challenges. Firstly, immunological responses require several cell types in different locations for proper development and take considerable time to develop. Secondly, immunological responses in outbred humans are characterized by genetic and functional variability. Still, the development and application of NAM are increasing rapidly, and the field is moving at such a fast pace that a special issue is timely. Our goal is to provide an overview of the current state-of-the-art regarding new approach methods or non-animal methods (NAM) in immunology. These should be inspired by the desire to mimic in vivo biology and describe e.g. challenges in mimicking immunological structures (like lymph nodes, bone marrow, local immune structures), immunological responses (systemic and local, innate and adaptive, B cells and T cells) and/or immunological processes (like maturation, trafficking, extravasation, immunotoxicity, affinity maturation).
Book Synopsis Mathematical Modeling of the Immune System in Homeostasis, Infection and Disease by : Gennady Bocharov
Download or read book Mathematical Modeling of the Immune System in Homeostasis, Infection and Disease written by Gennady Bocharov and published by Frontiers Media SA. This book was released on 2020-02-24 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The immune system provides the host organism with defense mechanisms against invading pathogens and tumor development and it plays an active role in tissue and organ regeneration. Deviations from the normal physiological functioning of the immune system can lead to the development of diseases with various pathologies including autoimmune diseases and cancer. Modern research in immunology is characterized by an unprecedented level of detail that has progressed towards viewing the immune system as numerous components that function together as a whole network. Currently, we are facing significant difficulties in analyzing the data being generated from high-throughput technologies for understanding immune system dynamics and functions, a problem known as the ‘curse of dimensionality’. As the mainstream research in mathematical immunology is based on low-resolution models, a fundamental question is how complex the mathematical models should be? To respond to this challenging issue, we advocate a hypothesis-driven approach to formulate and apply available mathematical modelling technologies for understanding the complexity of the immune system. Moreover, pure empirical analyses of immune system behavior and the system’s response to external perturbations can only produce a static description of the individual components of the immune system and the interactions between them. Shifting our view of the immune system from a static schematic perception to a dynamic multi-level system is a daunting task. It requires the development of appropriate mathematical methodologies for the holistic and quantitative analysis of multi-level molecular and cellular networks. Their coordinated behavior is dynamically controlled via distributed feedback and feedforward mechanisms which altogether orchestrate immune system functions. The molecular regulatory loops inherent to the immune system that mediate cellular behaviors, e.g. exhaustion, suppression, activation and tuning, can be analyzed using mathematical categories such as multi-stability, switches, ultra-sensitivity, distributed system, graph dynamics, or hierarchical control. GB is supported by the Russian Science Foundation (grant 18-11-00171). AM is also supported by grants from the Spanish Ministry of Economy, Industry and Competitiveness and FEDER grant no. SAF2016-75505-R, the “María de Maeztu” Programme for Units of Excellence in R&D (MDM-2014-0370) and the Russian Science Foundation (grant 18-11-00171).
Book Synopsis A Survey of Models for Tumor-Immune System Dynamics by : John A. Adam
Download or read book A Survey of Models for Tumor-Immune System Dynamics written by John A. Adam and published by Springer Science & Business Media. This book was released on 2012-10-06 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modeling and Immunology An enormous amount of human effort and economic resources has been directed in this century to the fight against cancer. The purpose, of course, has been to find strategies to overcome this hard, challenging and seemingly endless struggle. We can readily imagine that even greater efforts will be required in the next century. The hope is that ultimately humanity will be successful; success will have been achieved when it is possible to activate and control the immune system in its competition against neoplastic cells. Dealing with the above-mentioned problem requires the fullest pos sible cooperation among scientists working in different fields: biology, im munology, medicine, physics and, we believe, mathematics. Certainly, bi ologists and immunologists will make the greatest contribution to the re search. However, it is now increasingly recognized that mathematics and computer science may well able to make major contributions to such prob lems. We cannot expect mathematicians alone to solve fundamental prob lems in immunology and (in particular) cancer research, but valuable sup port, however modest, can be provided by mathematicians to the research aspirations of biologists and immunologists working in this field.
Book Synopsis An Introduction to Mathematical Modeling by : Edward A. Bender
Download or read book An Introduction to Mathematical Modeling written by Edward A. Bender and published by Courier Corporation. This book was released on 2012-05-23 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.
Book Synopsis Theoretical Immunology (part I) by : Alan Perelson
Download or read book Theoretical Immunology (part I) written by Alan Perelson and published by Westview Press. This book was released on 1988-01-21 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assuming that the complex phenomena underlying the operation of the immune system may be better understood through the collaborative efforts of theorists and experimentalists viewing the same phenomen
Book Synopsis Mathematical Methods and Models in Biomedicine by : Urszula Ledzewicz
Download or read book Mathematical Methods and Models in Biomedicine written by Urszula Ledzewicz and published by Springer Science & Business Media. This book was released on 2012-10-21 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical biomedicine is a rapidly developing interdisciplinary field of research that connects the natural and exact sciences in an attempt to respond to the modeling and simulation challenges raised by biology and medicine. There exist a large number of mathematical methods and procedures that can be brought in to meet these challenges and this book presents a palette of such tools ranging from discrete cellular automata to cell population based models described by ordinary differential equations to nonlinear partial differential equations representing complex time- and space-dependent continuous processes. Both stochastic and deterministic methods are employed to analyze biological phenomena in various temporal and spatial settings. This book illustrates the breadth and depth of research opportunities that exist in the general field of mathematical biomedicine by highlighting some of the fascinating interactions that continue to develop between the mathematical and biomedical sciences. It consists of five parts that can be read independently, but are arranged to give the reader a broader picture of specific research topics and the mathematical tools that are being applied in its modeling and analysis. The main areas covered include immune system modeling, blood vessel dynamics, cancer modeling and treatment, and epidemiology. The chapters address topics that are at the forefront of current biomedical research such as cancer stem cells, immunodominance and viral epitopes, aggressive forms of brain cancer, or gene therapy. The presentations highlight how mathematical modeling can enhance biomedical understanding and will be of interest to both the mathematical and the biomedical communities including researchers already working in the field as well as those who might consider entering it. Much of the material is presented in a way that gives graduate students and young researchers a starting point for their own work.
Book Synopsis Mathematical Biology by : Avner Friedman
Download or read book Mathematical Biology written by Avner Friedman and published by American Mathematical Soc.. This book was released on 2018-06-14 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast growing field of mathematical biology addresses biological questions using mathematical models from areas such as dynamical systems, probability, statistics, and discrete mathematics. This book considers models that are described by systems of partial differential equations, and it focuses on modeling, rather than on numerical methods and simulations. The models studied are concerned with population dynamics, cancer, risk of plaque growth associated with high cholesterol, and wound healing. A rich variety of open problems demonstrates the exciting challenges and opportunities for research at the interface of mathematics and biology. This book primarily addresses students and researchers in mathematics who do not necessarily have any background in biology and who may have had little exposure to PDEs.
Book Synopsis Dynamical Models in Biology by : Miklós Farkas
Download or read book Dynamical Models in Biology written by Miklós Farkas and published by Academic Press. This book was released on 2001-06-15 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic Models in Biology offers an introduction to modern mathematical biology. This book provides a short introduction to modern mathematical methods in modeling dynamical phenomena and treats the broad topics of population dynamics, epidemiology, evolution, immunology, morphogenesis, and pattern formation. Primarily employing differential equations, the author presents accessible descriptions of difficult mathematical models. Recent mathematical results are included, but the author's presentation gives intuitive meaning to all the main formulae. Besides mathematicians who want to get acquainted with this relatively new field of applications, this book is useful for physicians, biologists, agricultural engineers, and environmentalists. Key Topics Include: - Chaotic dynamics of populations - The spread of sexually transmitted diseases - Problems of the origin of life - Models of immunology - Formation of animal hide patterns - The intuitive meaning of mathematical formulae explained with many figures - Applying new mathematical results in modeling biological phenomena Miklos Farkas is a professor at Budapest University of Technology where he has researched and instructed mathematics for over thirty years. He has taught at universities in the former Soviet Union, Canada, Australia, Venezuela, Nigeria, India, and Columbia. Prof. Farkas received the 1999 Bolyai Award of the Hungarian Academy of Science and the 2001 Albert Szentgyorgyi Award of the Hungarian Ministry of Education. - A 'down-to-earth' introduction to the growing field of modern mathematical biology - Also includes appendices which provide background material that goes beyond advanced calculus and linear algebra
Book Synopsis A Biologist's Guide to Mathematical Modeling in Ecology and Evolution by : Sarah P. Otto
Download or read book A Biologist's Guide to Mathematical Modeling in Ecology and Evolution written by Sarah P. Otto and published by Princeton University Press. This book was released on 2011-09-19 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available
Book Synopsis Mathematical Models in Biology by : Elizabeth Spencer Allman
Download or read book Mathematical Models in Biology written by Elizabeth Spencer Allman and published by Cambridge University Press. This book was released on 2004 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introductory textbook on mathematical biology focuses on discrete models across a variety of biological subdisciplines. Biological topics treated include linear and non-linear models of populations, Markov models of molecular evolution, phylogenetic tree construction, genetics, and infectious disease models. The coverage of models of molecular evolution and phylogenetic tree construction from DNA sequence data is unique among books at this level. Computer investigations with MATLAB are incorporated throughout, in both exercises and more extensive projects, to give readers hands-on experience with the mathematical models developed. MATLAB programs accompany the text. Mathematical tools, such as matrix algebra, eigenvector analysis, and basic probability, are motivated by biological models and given self-contained developments, so that mathematical prerequisites are minimal.
Book Synopsis Mathematical Models of Tumor-Immune System Dynamics by : Amina Eladdadi
Download or read book Mathematical Models of Tumor-Immune System Dynamics written by Amina Eladdadi and published by Springer. This book was released on 2014-11-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of papers offers a broad synopsis of state-of-the-art mathematical methods used in modeling the interaction between tumors and the immune system. These papers were presented at the four-day workshop on Mathematical Models of Tumor-Immune System Dynamics held in Sydney, Australia from January 7th to January 10th, 2013. The workshop brought together applied mathematicians, biologists, and clinicians actively working in the field of cancer immunology to share their current research and to increase awareness of the innovative mathematical tools that are applicable to the growing field of cancer immunology. Recent progress in cancer immunology and advances in immunotherapy suggest that the immune system plays a fundamental role in host defense against tumors and could be utilized to prevent or cure cancer. Although theoretical and experimental studies of tumor-immune system dynamics have a long history, there are still many unanswered questions about the mechanisms that govern the interaction between the immune system and a growing tumor. The multidimensional nature of these complex interactions requires a cross-disciplinary approach to capture more realistic dynamics of the essential biology. The papers presented in this volume explore these issues and the results will be of interest to graduate students and researchers in a variety of fields within mathematical and biological sciences.
Book Synopsis Computational Immunology by : Josep Bassaganya-Riera
Download or read book Computational Immunology written by Josep Bassaganya-Riera and published by Academic Press. This book was released on 2015-10-21 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Immunology: Models and Tools encompasses the methodological framework and application of cutting-edge tools and techniques to study immunological processes at a systems level, along with the concept of multi-scale modeling. The book's emphasis is on selected cases studies and application of the most updated technologies in computational modeling, discussing topics such as computational modeling and its usage in immunological research, bioinformatics infrastructure, ODE based modeling, agent based modeling, and high performance computing, data analytics, and multiscale modeling. There are also modeling exercises using recent tools and models which lead the readers to a thorough comprehension and applicability. The book is a valuable resource for immunologists, computational biologists, bioinformaticians, biotechnologists, and computer scientists, as well as all those who wish to broaden their knowledge in systems modeling. - Offers case studies with different levels of complexity - Provides a detailed view on cutting-edge tools for modeling that are useful to experimentalists with limited computational skills - Explores the usage of simulation for hypothesis generation, helping the reader to understand the most valuable points on experimental setting
Book Synopsis Computational Immunology by : Shyamasree Ghosh
Download or read book Computational Immunology written by Shyamasree Ghosh and published by CRC Press. This book was released on 2020-01-31 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Immunology: Applications focuses on different mathematical models, statistical tools, techniques, and computational modelling that helps in understanding complex phenomena of the immune system and its biological functions. The book also focuses on the latest developments in computational biology in designing of drugs, targets, biomarkers for early detection and prognosis of a disease. It highlights the applications of computational methods in deciphering the complex processes of the immune system and its role in health and disease. This book discusses the most essential topics, including Next generation sequencing (NGS) and computational immunology Computational modelling and biology of diseases Drug designing Computation and identification of biomarkers Application in organ transplantation Application in disease detection and therapy Computational methods and applications in understanding of the invertebrate immune system S Ghosh is MSc, PhD, PGDHE, PGDBI, is PhD from IICB, CSIR, Kolkata, awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.
Book Synopsis Mathematical Methods for Physicists by : George Brown Arfken
Download or read book Mathematical Methods for Physicists written by George Brown Arfken and published by Academic Press. This book was released on 2013 with total page 1230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of Contents Mathematical Preliminaries Determinants and Matrices Vector Analysis Tensors and Differential Forms Vector Spaces Eigenvalue Problems Ordinary Differential Equations Partial Differential Equations Green's Functions Complex Variable Theory Further Topics in Analysis Gamma Function Bessel Functions Legendre Functions Angular Momentum Group Theory More Special Functions Fourier Series Integral Transforms Periodic Systems Integral Equations Mathieu Functions Calculus of Variations Probability and Statistics.
