Mathematical Modelling in Biomedicine

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Publisher : MDPI
ISBN 13 : 3039434934
Total Pages : 224 pages
Book Rating : 4.30/5 ( download)

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Book Synopsis Mathematical Modelling in Biomedicine by : Vitaly Volpert

Download or read book Mathematical Modelling in Biomedicine written by Vitaly Volpert and published by MDPI. This book was released on 2021-01-26 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mathematical Methods and Models in Biomedicine

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Publisher : Springer Science & Business Media
ISBN 13 : 1461441773
Total Pages : 426 pages
Book Rating : 4.79/5 ( download)

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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.

Mathematical Modelling in Biomedicine

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Publisher : Springer Science & Business Media
ISBN 13 : 9789027721495
Total Pages : 286 pages
Book Rating : 4.91/5 ( download)

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Book Synopsis Mathematical Modelling in Biomedicine by : Y. Cherruault

Download or read book Mathematical Modelling in Biomedicine written by Y. Cherruault and published by Springer Science & Business Media. This book was released on 1986-02-28 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Approach your problems from the right It isn't that they can't see the solution. It end and begin with the answers. Then is that they can't see the problem. one day, perhaps you will find the final question. G.K. Chesterton. The Scandal of Father Brown 'The point of a Pin'. 'The Hermit Clad in Crane Feathers' in R. van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, cod ing theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical pro gramming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces.

Mathematical Modelling in Biomedicine

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Publisher : Springer Science & Business Media
ISBN 13 : 9400954921
Total Pages : 273 pages
Book Rating : 4.22/5 ( download)

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Book Synopsis Mathematical Modelling in Biomedicine by : Y. Cherruault

Download or read book Mathematical Modelling in Biomedicine written by Y. Cherruault and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Approach your problems from the right It isn't that they can't see the solution. It end and begin with the answers. Then is that they can't see the problem. one day, perhaps you will find the final question. G.K. Chesterton. The Scandal of Father Brown 'The point of a Pin'. 'The Hermit Clad in Crane Feathers' in R. van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, cod ing theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical pro gramming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces.

Mathematical Modelling in Biomedicine

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Publisher :
ISBN 13 : 9783039434947
Total Pages : 224 pages
Book Rating : 4.42/5 ( download)

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Book Synopsis Mathematical Modelling in Biomedicine by : Vitaly Volpert

Download or read book Mathematical Modelling in Biomedicine written by Vitaly Volpert and published by . This book was released on 2021 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mathematical Models and Computer Simulations for Biomedical Applications

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Publisher : Springer Nature
ISBN 13 : 3031357159
Total Pages : 261 pages
Book Rating : 4.52/5 ( download)

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Book Synopsis Mathematical Models and Computer Simulations for Biomedical Applications by : Gabriella Bretti

Download or read book Mathematical Models and Computer Simulations for Biomedical Applications written by Gabriella Bretti and published by Springer Nature. This book was released on 2023-09-17 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical modelling and computer simulations are playing a crucial role in the solution of the complex problems arising in the field of biomedical sciences and provide a support to clinical and experimental practices in an interdisciplinary framework. Indeed, the development of mathematical models and efficient numerical simulation tools is of key importance when dealing with such applications. Moreover, since the parameters in biomedical models have peculiar scientific interpretations and their values are often unknown, accurate estimation techniques need to be developed for parameter identification against the measured data of observed phenomena. In the light of the new challenges brought by the biomedical applications, computational mathematics paves the way for the validation of the mathematical models and the investigation of control problems. The volume hosts high-quality selected contributions containing original research results as well as comprehensive papers and survey articles including prospective discussion focusing on some topical biomedical problems. It is addressed, but not limited to: research institutes, academia, and pharmaceutical industries.

Mathematical Models for Biomedicine

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Publisher :
ISBN 13 : 9788892332980
Total Pages : 432 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Mathematical Models for Biomedicine by : Luca Mesin

Download or read book Mathematical Models for Biomedicine written by Luca Mesin and published by . This book was released on 2017 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modeling in Computational Biology and Biomedicine

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Publisher : Springer Science & Business Media
ISBN 13 : 364231208X
Total Pages : 333 pages
Book Rating : 4.83/5 ( download)

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Book Synopsis Modeling in Computational Biology and Biomedicine by : Frédéric Cazals

Download or read book Modeling in Computational Biology and Biomedicine written by Frédéric Cazals and published by Springer Science & Business Media. This book was released on 2012-11-06 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Model-Based Hypothesis Testing in Biomedicine

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Publisher : Linköping University Electronic Press
ISBN 13 : 9176854574
Total Pages : 102 pages
Book Rating : 4.70/5 ( download)

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Book Synopsis Model-Based Hypothesis Testing in Biomedicine by : Rikard Johansson

Download or read book Model-Based Hypothesis Testing in Biomedicine written by Rikard Johansson and published by Linköping University Electronic Press. This book was released on 2017-10-03 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: The utilization of mathematical tools within biology and medicine has traditionally been less widespread compared to other hard sciences, such as physics and chemistry. However, an increased need for tools such as data processing, bioinformatics, statistics, and mathematical modeling, have emerged due to advancements during the last decades. These advancements are partly due to the development of high-throughput experimental procedures and techniques, which produce ever increasing amounts of data. For all aspects of biology and medicine, these data reveal a high level of inter-connectivity between components, which operate on many levels of control, and with multiple feedbacks both between and within each level of control. However, the availability of these large-scale data is not synonymous to a detailed mechanistic understanding of the underlying system. Rather, a mechanistic understanding is gained first when we construct a hypothesis, and test its predictions experimentally. Identifying interesting predictions that are quantitative in nature, generally requires mathematical modeling. This, in turn, requires that the studied system can be formulated into a mathematical model, such as a series of ordinary differential equations, where different hypotheses can be expressed as precise mathematical expressions that influence the output of the model. Within specific sub-domains of biology, the utilization of mathematical models have had a long tradition, such as the modeling done on electrophysiology by Hodgkin and Huxley in the 1950s. However, it is only in recent years, with the arrival of the field known as systems biology that mathematical modeling has become more commonplace. The somewhat slow adaptation of mathematical modeling in biology is partly due to historical differences in training and terminology, as well as in a lack of awareness of showcases illustrating how modeling can make a difference, or even be required, for a correct analysis of the experimental data. In this work, I provide such showcases by demonstrating the universality and applicability of mathematical modeling and hypothesis testing in three disparate biological systems. In Paper II, we demonstrate how mathematical modeling is necessary for the correct interpretation and analysis of dominant negative inhibition data in insulin signaling in primary human adipocytes. In Paper III, we use modeling to determine transport rates across the nuclear membrane in yeast cells, and we show how this technique is superior to traditional curve-fitting methods. We also demonstrate the issue of population heterogeneity and the need to account for individual differences between cells and the population at large. In Paper IV, we use mathematical modeling to reject three hypotheses concerning the phenomenon of facilitation in pyramidal nerve cells in rats and mice. We also show how one surviving hypothesis can explain all data and adequately describe independent validation data. Finally, in Paper I, we develop a method for model selection and discrimination using parametric bootstrapping and the combination of several different empirical distributions of traditional statistical tests. We show how the empirical log-likelihood ratio test is the best combination of two tests and how this can be used, not only for model selection, but also for model discrimination. In conclusion, mathematical modeling is a valuable tool for analyzing data and testing biological hypotheses, regardless of the underlying biological system. Further development of modeling methods and applications are therefore important since these will in all likelihood play a crucial role in all future aspects of biology and medicine, especially in dealing with the burden of increasing amounts of data that is made available with new experimental techniques. Användandet av matematiska verktyg har inom biologi och medicin traditionellt sett varit mindre utbredd jämfört med andra ämnen inom naturvetenskapen, såsom fysik och kemi. Ett ökat behov av verktyg som databehandling, bioinformatik, statistik och matematisk modellering har trätt fram tack vare framsteg under de senaste decennierna. Dessa framsteg är delvis ett resultat av utvecklingen av storskaliga datainsamlingstekniker. Inom alla områden av biologi och medicin så har dessa data avslöjat en hög nivå av interkonnektivitet mellan komponenter, verksamma på många kontrollnivåer och med flera återkopplingar både mellan och inom varje nivå av kontroll. Tillgång till storskaliga data är emellertid inte synonymt med en detaljerad mekanistisk förståelse för det underliggande systemet. Snarare uppnås en mekanisk förståelse först när vi bygger en hypotes vars prediktioner vi kan testa experimentellt. Att identifiera intressanta prediktioner som är av kvantitativ natur, kräver generellt sett matematisk modellering. Detta kräver i sin tur att det studerade systemet kan formuleras till en matematisk modell, såsom en serie ordinära differentialekvationer, där olika hypoteser kan uttryckas som precisa matematiska uttryck som påverkar modellens output. Inom vissa delområden av biologin har utnyttjandet av matematiska modeller haft en lång tradition, såsom den modellering gjord inom elektrofysiologi av Hodgkin och Huxley på 1950?talet. Det är emellertid just på senare år, med ankomsten av fältet systembiologi, som matematisk modellering har blivit ett vanligt inslag. Den något långsamma adapteringen av matematisk modellering inom biologi är bl.a. grundad i historiska skillnader i träning och terminologi, samt brist på medvetenhet om exempel som illustrerar hur modellering kan göra skillnad och faktiskt ofta är ett krav för en korrekt analys av experimentella data. I detta arbete tillhandahåller jag sådana exempel och demonstrerar den matematiska modelleringens och hypotestestningens allmängiltighet och tillämpbarhet i tre olika biologiska system. I Arbete II visar vi hur matematisk modellering är nödvändig för en korrekt tolkning och analys av dominant-negativ-inhiberingsdata vid insulinsignalering i primära humana adipocyter. I Arbete III använder vi modellering för att bestämma transporthastigheter över cellkärnmembranet i jästceller, och vi visar hur denna teknik är överlägsen traditionella kurvpassningsmetoder. Vi demonstrerar också frågan om populationsheterogenitet och behovet av att ta hänsyn till individuella skillnader mellan celler och befolkningen som helhet. I Arbete IV använder vi matematisk modellering för att förkasta tre hypoteser om hur fenomenet facilitering uppstår i pyramidala nervceller hos råttor och möss. Vi visar också hur en överlevande hypotes kan beskriva all data, inklusive oberoende valideringsdata. Slutligen utvecklar vi i Arbete I en metod för modellselektion och modelldiskriminering med hjälp av parametrisk ”bootstrapping” samt kombinationen av olika empiriska fördelningar av traditionella statistiska tester. Vi visar hur det empiriska ”log-likelihood-ratio-testet” är den bästa kombinationen av två tester och hur testet är applicerbart, inte bara för modellselektion, utan också för modelldiskriminering. Sammanfattningsvis är matematisk modellering ett värdefullt verktyg för att analysera data och testa biologiska hypoteser, oavsett underliggande biologiskt system. Vidare utveckling av modelleringsmetoder och tillämpningar är därför viktigt eftersom dessa sannolikt kommer att spela en avgörande roll i framtiden för biologi och medicin, särskilt när det gäller att hantera belastningen från ökande datamängder som blir tillgänglig med nya experimentella tekniker.

Biomathematics

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Publisher : World Scientific
ISBN 13 : 9812774858
Total Pages : 525 pages
Book Rating : 4.59/5 ( download)

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Book Synopsis Biomathematics by : J. C. Misra

Download or read book Biomathematics written by J. C. Misra and published by World Scientific. This book was released on 2006 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on modelling and simulation in biomathematics will be invaluable to researchers who are interested in the emerging areas of the field. Graduate students in related areas as well as lecturers will also find it beneficial. Some of the chapters have been written by distinguished experts in the field. Sample Chapter(s). Chapter 1: Detecting Mosaic Structures in DNA Sequence Alignments (1,349 KB). Contents: Detecting Mosaic Structures in DNA Sequence Alignments (D Husmeier); Application of Statistical Methodology and Model Design to Socio-Behaviour of HIV Transmission (J Oluwoye); A Stochastic Model Incorporating HIV Treatments for a Heterosexual Population: Impact on Threshold Conditions (R J Gallop et al.); Modeling and Identification of the Dynamics of the MF-Influenced Free-Radical Transformations in Lipid-Modeling Substances and Lipids (J Bentsman et al.); Computer Simulation of Self-Reorganization in Biological Cells (D Greenspan); Modelling Biological Gel Contraction by Cells: Consequences of Cell Traction Forces Distribution and Initial Stress (S Ramtani); Peristaltic Transport of Physiological Fluids (J C Misra & S K Pandey); Mathematical Modelling of DNA Knots and Links (J C Misra & S Mukherjee); Using Monodomain Computer Models for the Simulation of Electric Fields During Excitation Spread in Cardiac Tissue (G Plank); Flow in Tubes with Complicated Geometries with Special Application to Blood Flow in Large Arteries (G Jayaraman); Mathematical Modeling in Reproductive Biomedicine (S Sharma & S K Guha); Image Theory and Applications in Bioelectromagnetics (P D Einziger et al.); Dynamics of Humanoid Robots: Geometrical and Topological Duality (V G Ivancevic); The Effects of Body Composition on Energy Expenditure and Weight Dynamics During Hypophagia: A Setpoint Analysis (F P Kozusko); Mathematical Models in Population Dynamics and Ecology (R Diluo); Modelling in Bone Biomechanics (J C Misra & S Samanta). Readership: Graduate students, academic and researchers in biomathematics, mathematical biology, mathematical modeling, biotechnology, biocomputing, biophysics, bioengineering and mechanics."