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Author: John A. Adam
Publisher: Springer Science & Business Media
ISBN: 0817681191
Category : Mathematics
Languages : en
Pages : 357
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Book Description
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.
Author: John A. Adam
Publisher: Springer Science & Business Media
ISBN: 0817681191
Category : Mathematics
Languages : en
Pages : 357
Get Book
Book Description
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.
Author: John A. Adam
Publisher: Birkhauser
ISBN: 9783764339012
Category : Tumors
Languages : en
Pages : 344
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Book Description
This unique book is a collection of seven interdisciplinary surveys on modeling tumor dynamics and interactions between tumors and immune system. The goal is to provide an accessible, comprehensive report on the field and to help define a framework for future interdisciplinary research activity. Modeling and simulation of general behaviors of immune systems are also discussed. Each survey carefully covers a specialized field and provides a detailed description of the present state-of-the-art in research. The reader will be able to obtain essential information on the methodological approach used and on the models that are categorized and used. The book is an excellent resource and survey for applied mathematicians, mathematical biologists and biologists interested in modeling methods in immunology and related sciences.
Author: Amina Eladdadi
Publisher: Springer
ISBN: 1493917935
Category : Mathematics
Languages : en
Pages : 275
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Book Description
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.
Author: Gennady Bocharov
Publisher: Frontiers Media SA
ISBN: 2889634612
Category :
Languages : en
Pages : 278
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Book Description
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).
Author: John A. Adam
Publisher: Princeton University Press
ISBN: 1400841011
Category : Mathematics
Languages : en
Pages : 408
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Book Description
From rainbows, river meanders, and shadows to spider webs, honeycombs, and the markings on animal coats, the visible world is full of patterns that can be described mathematically. Examining such readily observable phenomena, this book introduces readers to the beauty of nature as revealed by mathematics and the beauty of mathematics as revealed in nature. Generously illustrated, written in an informal style, and replete with examples from everyday life, Mathematics in Nature is an excellent and undaunting introduction to the ideas and methods of mathematical modeling. It illustrates how mathematics can be used to formulate and solve puzzles observed in nature and to interpret the solutions. In the process, it teaches such topics as the art of estimation and the effects of scale, particularly what happens as things get bigger. Readers will develop an understanding of the symbiosis that exists between basic scientific principles and their mathematical expressions as well as a deeper appreciation for such natural phenomena as cloud formations, halos and glories, tree heights and leaf patterns, butterfly and moth wings, and even puddles and mud cracks. Developed out of a university course, this book makes an ideal supplemental text for courses in applied mathematics and mathematical modeling. It will also appeal to mathematics educators and enthusiasts at all levels, and is designed so that it can be dipped into at leisure.
Author: Thomas S. Deisboeck
Publisher: CRC Press
ISBN: 9781439814420
Category : Mathematics
Languages : en
Pages : 484
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Book Description
Cancer is a complex disease process that spans multiple scales in space and time. Driven by cutting-edge mathematical and computational techniques, in silico biology provides powerful tools to investigate the mechanistic relationships of genes, cells, and tissues. It enables the creation of experimentally testable hypotheses, the integration of data across scales, and the prediction of tumor progression and treatment outcome (in silico oncology). Drawing on an interdisciplinary group of distinguished international experts, Multiscale Cancer Modeling discusses the scientific and technical expertise necessary to conduct innovative cancer modeling research across scales. It presents contributions from some of the top in silico modeling groups in the United States and Europe. The ultimate goal of multiscale modeling and simulation approaches is their use in clinical practice, such as supporting patient-specific treatment optimization. This volume covers state-of-the-art methods of multiscale cancer modeling and addresses the field’s potential as well as future challenges. It encourages collaborations among researchers in various disciplines to achieve breakthroughs in cancer modeling.
Author: Yang Kuang
Publisher: CRC Press
ISBN: 1498752977
Category : Mathematics
Languages : en
Pages : 291
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Book Description
Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding, the text describes well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure, such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models, including cell quota-based population growth models, with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses, this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways, including a single-semester undergraduate course, a more ambitious graduate course, or a full-year sequence on mathematical oncology.
Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3030341526
Category : Technology & Engineering
Languages : en
Pages : 903
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Book Description
This book describes the latest advances in intelligent techniques such as fuzzy logic, neural networks, and optimization algorithms, and their relevance in building intelligent information systems in combination with applied mathematics. The authors also outline the applications of these systems in areas like intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. By sharing fresh ideas and identifying new targets/problems it offers young researchers and students new directions for their future research. The book is intended for readers from mathematics and computer science, in particular professors and students working on theory and applications of intelligent systems for real-world applications.
Author: Marta Bertolaso
Publisher: Springer
ISBN: 9402408657
Category : Philosophy
Languages : en
Pages : 190
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Book Description
Since the 1970s, the origin of cancer is being explored from the point of view of the Somatic Mutation Theory (SMT), focusing on genetic mutations and clonal expansion of somatic cells. As cancer research expanded in several directions, the dominant focus on cells remained steady, but the classes of genes and the kinds of extra-genetic factors that were shown to have causal relevance in the onset of cancer multiplied. The wild heterogeneity of cancer-related mutations and phenotypes, along with the increasing complication of models, led to an oscillation between the hectic search of ‘the’ few key factors that cause cancer and the discouragement in face of a seeming ‘endless complexity’. To tame this complexity, cancer research started to avail itself of the tools that were being developed by Systems Biology. At the same time, anti-reductionist voices began claiming that cancer research was stuck in a sterile research paradigm. This alternative discourse even gave birth to an alternative theory: the Tissue Organization Field Theory (TOFT). A deeper philosophical analysis shows limits and possibilities of reductionist and anti-reductionist positions and of their polarization. This book demonstrates that a radical philosophical reflection is necessary to drive cancer research out of its impasses. At the very least, this will be a reflection on the assumptions of different kinds of cancer research, on the implications of what cancer research has been discovering over 40 years and more, on a view of scientific practice that is most able to make sense of the cognitive and social conflicts that are seen in the scientific community (and in its results), and, finally, on the nature of living entities with which we entertain this fascinating epistemological dance that we call scientific research. The proposed Dynamic and Relational View of carcinogenesis is a starting point in all these directions.
Author: Nicola Bellomo
Publisher: Springer Science & Business Media
ISBN: 0817647139
Category : Mathematics
Languages : en
Pages : 481
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Book Description
This collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena. Topics covered include stochastic evolutionary models of cancer initiation and progression, tumor cords and their response to anticancer agents, and immune competition in tumor progression and prevention. The complexity of modeling living matter requires the development of new mathematical methods and ideas. This volume, written by first-rate researchers in the field of mathematical biology, is one of the first steps in that direction.
