4 edition of Mathematical modeling in immunology and medicine found in the catalog.
Mathematical modeling in immunology and medicine
IFIP TC-7 Working Conference on Mathematical Modeling in Immunology and Medicine (1982 Moscow, R.S.F.S.R.)
by North-Holland Pub. Co., Sole distributors for the U.S.A. and Canada, Elsevier Science Pub. Co. in Amsterdam, New York, New York
Written in English
|Statement||edited by G.I. Marchuk and L.N. Belykh.|
|Contributions||Marchuk, G. I. 1925-, Belykh, L. N. 1953-, IFIP TC-7 (Organization), Akademii͡a︡ nauk SSSR.|
|LC Classifications||QR182.2.M36 I34 1982|
|The Physical Object|
|Pagination||x, 396 p. :|
|Number of Pages||396|
|LC Control Number||83002219|
Combining radiotherapy with immune checkpoint blockade may offer considerable therapeutic impact if the immunosuppressive nature of the tumor microenvironment (TME) can be relieved. In this study, we used mathematical models, which can illustrate the potential synergism between immune checkpoint inhibitors and radiotherapy. A discrete-time pharmacodynamic model of the combination of. Mathematical Modelling. Mathematical modelling is the activity by which a problem involving the real-world is translated into mathematics to form a model which can then be used to provide information about the original real problem. From: Mathematics for Engineers and Technologists, Related terms: Energy Engineering; Mathematical Model.
Mathematical models can be profoundly helpful tools to make public health decisions and ensure optimal use of resources to reduce the morbidity and mortality associated with the COVID pandemic, but only if they are rigorously evaluated and valid and their projections are robust and reliable. A mathematical model of combined CD8 T cell costimulation by BB (CD) and OX40 (CD) receptors. Center for Quantitative Medicine, School of Medicine, UConn Health, Farmington Ave., Farmington, CT, USA. [email protected] (2)Department of Immunology, School of Medicine, UConn Health, Farmington Ave., Farmington, CT.
The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Papers should either provide biological insight as a result of mathematical analysis or identify and open up challenging new types of mathematical problems that derive from biological knowledge (in the form of . Mathematical models are powerful because they provide a method to explain past experiments and predict the outcomes of future experiments. A commonly used approach in microbial ecology literature is to develop correlation-based networks to describe the co-occurrence and dynamics of populations (6 – 8).
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Role of mathematical models in immunology There are many viewpoints in regard to the purpose of developing mathematical models to describe immunological phenomena: from explaining existing observations and generating new hypotheses that can be tested empirically (Ankomah and Levin ), to understanding which assumptions in the model are useful and generate outcomes Cited by: The authors then introduce the modeling of experimental and human infections and provide the reader with helpful exercises.
The target audience primarily comprises researchers and graduate students in the field of mathematical biology who wish to be concisely introduced into mathematical by: 6. Mathematical Modeling of the Immune Response: Medicine & Health Sciences Mathematical Modeling of the Immune Response presents a comprehensive examination of the history of development of mathematical models in immunology and discusses how these models are used by biologists.
The book features the results of work done by Cited by: A mathematical model is a description of a system using mathematical concepts and process of developing a mathematical model is termed mathematical atical models are used in the natural sciences (such as physics, biology, earth science, chemistry) and engineering disciplines (such as computer science, electrical engineering), as well as in the social sciences (such.
Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. Connections are made between diverse biological examples linked by common mathematical themes, exploring a variety of discrete and continuous ordinary and partial differential equation by: This book differs from almost all other available modeling books in that the author addresses both mechanistic and statistical models as well as "hybrid" models.
Since many problems coming out of industrial and medical applications in recent years require hybrid models, this text is timely. This JCO CCI Special Collection on Mathematical Oncology can be grouped into three broad categories that connect to themes in contemporary cancer research: 1) modeling the relationship between cancer therapy and the immune system; 2) optimizing personalized medicine through clinical imaging and predictive mathematical modeling; and 3.
Over the last few decades, there have been significant developments in theoretical, experimental, and clinical approaches to understand the dynamics of cancer cells and their interactions with the immune system.
These have led to the development of important methods for cancer therapy including virotherapy, immunotherapy, chemotherapy, targeted drug therapy, and many others.
1. Introduction. Mathematics has a long tradition in biology and medicine, going back at least to Gregor Mendel's work in genetics and Theodor Boveri's work on the nature of the chromosomes .However, as the various subfields have become more specialized, and understanding of biological systems more detailed, modelling has often been dismissed or ‘regarded with suspicion, partly.
Cholera, an acute gastro-intestinal infection and a waterborne disease continues to emerge in developing countries and remains an important global health challenge. In this paper, we formulate a mathematical model that captures some essential dynamics of cholera transmission with public health educational campaigns, vaccination, sanitation and treatment as control strategies in.
Leonid, H: Handbook Of Cancer Models With Applications Series in Mathematical Biology and Medicine, Band 9: : Hanin, Leonid, Tan, Wai-Yuan: Fremdsprachige Bücher. Mathematical and theoretical biology is a branch of biology which employs theoretical analysis, mathematical models and abstractions of the living organisms to investigate the principles that govern the structure, development and behavior of the systems, as opposed to experimental biology which deals with the conduction of experiments to prove and validate the scientific theories.
Interaction of the immune system with a target population of, e.g., bacteria, viruses, antigens, or tumor cells must be considered as a dynamic process. We describe this process by a system of two ordinary differential equations.
Although the model is strongly idealized it demonstrates how the combination of a few proposed nonlinear interaction rules between the immune system and its targets. A simple mathematical model including only effector cells making TNF-α, regulatory cells producing an inhibitor of TNF-α such as sTNFR and an activation signal from the allogeneic transplant gave rise to fluctuations in TNF production similar to those found experimentally.
14 Even such a simple model may help explain spiking temperature. In testing mathematical models against real data, we often have the situation of having to check whether data fits an equation.
If the relationship is linear, i.e. of the form y = mx + c, then it is comparatively easy to see whether the data fits the straight line and to ascertain the gradient m and intercept r, if the relationship is non-linear this is not so easy.
* Innovative Mathematical Methods and Education. Both volumes will be excellent reference texts for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.
"The book's emphasis is on mathematical techniques for the analysis of given models Illustrations are simple, but relevant and clear Although the authors claim that "the monograph id designed to introduce probabilists and statisticians to the diverse models describing the spread of epidemics and rumours in a population", the clarity of Reviews: 4.
Mathematical Modeling in Systems Biology: An Introduction (The MIT Press): Medicine & Health Science Books @ iews: 5. This monograph concisely but thoroughly introduces the reader to the field of mathematical immunology.
The book covers first basic principles of formulating a mathematical model, and an outline on data-driven parameter estimation and model selection. The authors then introduce the modeling of experimental and human infections and provide the. Computational Mathematics and Modeling presents research in numerical analysis, control theory, and the interplay of modeling and computational mathematics.
It features work by scientists from Moscow State University, an institution recognized worldwide for. Modelling biological systems is a significant task of systems biology and mathematical biology. Computational systems biology aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems.
It involves the use of computer simulations of biological systems, including cellular subsystems (such as the.We propose a new mathematical model describing a biotechnological process of simultaneous production of hydrogen and methane by anaerobic digestion.
The process is carried out in two connected continuously stirred bioreactors. The proposed model is developed by adapting and reducing the well known Anaerobic Digester Model No 1 (ADM1).
Mathematical analysis of the model is carried out.The authors then introduce the modeling of experimental and human infections and provide the reader with helpful exercises. The target audience primarily comprises researchers and graduate students in the field of mathematical biology who wish to be concisely introduced into mathematical immunology.