Selected Topics in Cancer Modeling PDF Download

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.

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: 1315361981
Category : Mathematics
Languages : en
Pages : 472

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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: W. Y. Tan
Publisher: World Scientific
ISBN: 9812779485
Category : Political Science
Languages : en
Pages : 592

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Book Description
Composed of contributions from an international team of leading researchers, this book pulls together the most recent research results in the field of cancer modeling to provide readers with the most advanced mathematical models of cancer and their applications.Topics included in the book cover oncogenetic trees, stochastic multistage models of carcinogenesis, effects of ionizing radiation on cell cycle and genomic instability, induction of DNA damage by ionizing radiation and its repair, epigenetic cancer models, bystander effects of radiation, multiple pathway models of human colon cancer, and stochastic models of metastasis. The book also provides some important applications of cancer models to the assessment of cancer risk associated with various hazardous environmental agents, to cancer screening by MRI, and to drug resistance in cancer chemotherapy. An updated statistical design and analysis of xenograft experiments as well as a statistical analysis of cancer occult clinical data are also provided.The book will serve as a useful source of reference for researchers in biomathematics, biostatistics and bioinformatics; for clinical investigators and medical doctors employing quantitative methods to develop procedures for cancer diagnosis, prevention, control and treatment; and for graduate students.

Author: Beverly A. Teicher
Publisher: Springer Science & Business Media
ISBN: 1592591000
Category : Medical
Languages : en
Pages : 994

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Book Description
Beverly A. Teicher and a panel of leading experts comprehensively describe for the first time in many years the state-of-the-art in animal tumor model research. The wide array of models detailed form the basis for the selection of compounds and treatments that go into clinical testing of patients, and include syngeneic models, human tumor xenograft models, orthotopic models, metastatic models, transgenic models, and gene knockout models. Synthesizing many years experience with all the major in vivo models currently available for the study of malignant disease, Tumor Models in Cancer Research provides preclinical and clinical cancer researchers alike with a comprehensive guide to the selection of these models, their effective use, and the optimal interpretation of their results.

Author: Luigi Preziosi
Publisher: CRC Press
ISBN: 9780203494899
Category : Mathematics
Languages : en
Pages : 456

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Book Description
Understanding how cancer tumours develop and spread is vital for finding treatments and cures. Cancer Modelling and Simulation demonstrates how mathematical modelling and computer simulation techniques are used to discover and gain insight into the dynamics of tumour development and growth. It highlights the benefits of tumour modelling, such as discovering optimal tumour therapy schedules, identifying the most promising candidates for further clinical investigation, and reducing the number of animal experiments. By examining the analytical, mathematical, and biological aspects of tumour growth and modelling, the book provides a common language and knowledge for professionals in several disciplines.

Author: Dominik Wodarz
Publisher: World Scientific
ISBN: 9814566381
Category : Medical
Languages : en
Pages : 532

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Book Description
The book aims to provide an introduction to mathematical models that describe the dynamics of tumor growth and the evolution of tumor cells. It can be used as a textbook for advanced undergraduate or graduate courses, and also serves as a reference book for researchers. The book has a strong evolutionary component and reflects the viewpoint that cancer can be understood rationally through a combination of mathematical and biological tools. It can be used both by mathematicians and biologists. Mathematically, the book starts with relatively simple ordinary differential equation models, and subsequently explores more complex stochastic and spatial models. Biologically, the book starts with explorations of the basic dynamics of tumor growth, including competitive interactions among cells, and subsequently moves on to the evolutionary dynamics of cancer cells, including scenarios of cancer initiation, progression, and treatment. The book finishes with a discussion of advanced topics, which describe how some of the mathematical concepts can be used to gain insights into a variety of questions, such as epigenetics, telomeres, gene therapy, and social interactions of cancer cells. Contents:Teaching GuideCancer and Somatic EvolutionMathematical Modeling of TumorigenesisBasic Growth Dynamics and Deterministic Models:Single Species GrowthTwo-Species Competition DynamicsCompetition Between Genetically Stable and Unstable CellsChromosomal Instability and Tumor GrowthAngiogenesis Inhibitors, Promoters, and Spatial GrowthEvolutionary Dynamics and Stochastic Models:Evolutionary Dynamics of Tumor Initiation Through Oncogenes: The Gain-of-Function ModelEvolutionary Dynamics of Tumor Initiation Through Tumor-Suppressor Genes: The Loss-of-Function Model and Stochastic TunnelingMicrosatellite and Chromosomal Instability in Sporadic and Familial Colorectal CancersEvolutionary Dynamics in Hierarchical PopulationsSpatial Evolutionary Dynamics of Tumor InitiationComplex Tumor Dynamics in SpaceStochastic Modeling of Cellular Growth, Treatment, and Resistance GenerationEvolutionary Dynamics of Drug Resistance in Chronic Myeloid LeukemiaAdvanced Topics:Evolutionary Dynamics of Stem-Cell Driven Tumor GrowthTumor Growth Kinetics and Disease ProgressionEpigenetic Changes and the Rate of DNA MethylationTelomeres and Cancer ProtectionGene Therapy and Oncolytic Virus TherapyImmune Responses, Tumor Growth, and TherapiesTowards Higher Complexities: Social Interactions Readership: Researchers in mathematical biology, mathematical modeling, biology, mathematical oncology. Keywords:Mathematical Oncology;Dynamics;Evolution;Evolutionary Dynamics;Cancer;Mathematical Models;Somatic Evolution;TeachingKey Features:Both a reference book for the topic, and provides material for undergraduate and graduate coursesTries to bridge the divide between mathematicians and biologists, which is also reflected in the backgrounds of the two authorsShows how mathematical concepts can be translated into experimentally and clinically useful insightsRooted in evolutionary biology, the book handles this very complex phenomenon in an intuitive and mathematically elegant wayContains problems and research projects for each topic10 pages of figures in color

Author: Vittorio Cristini
Publisher: Cambridge University Press
ISBN: 1139491504
Category : Technology & Engineering
Languages : en
Pages : 299

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Book Description
Mathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth of cancer cells over multiple time and spatial scales. This book, the first to integrate state-of-the-art numerical techniques with experimental data, provides an in-depth assessment of tumor cell modeling at multiple scales. The first part of the text presents a detailed biological background with an examination of single-phase and multi-phase continuum tumor modeling, discrete cell modeling, and hybrid continuum-discrete modeling. In the final two chapters, the authors guide the reader through problem-based illustrations and case studies of brain and breast cancer, to demonstrate the future potential of modeling in cancer research. This book has wide interdisciplinary appeal and is a valuable resource for mathematical biologists, biomedical engineers and clinical cancer research communities wishing to understand this emerging field.

Author: Dominik Wodarz
Publisher: World Scientific
ISBN: 9814481874
Category : Science
Languages : en
Pages : 266

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Book Description
The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of cells, genetic instability, and angiogenesis. The book also discusses the use of mathematical models for the analysis of therapeutic approaches such as chemotherapy, immunotherapy, and the use of oncolytic viruses.

Author: Michael Breitenbach
Publisher: Frontiers Media SA
ISBN: 288945701X
Category :
Languages : en
Pages : 176

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Book Description
Cancer research, like research on other diseases, highly depends on representative and reliable model systems. In the Research Topic “Cancer Models”, we collected original papers and review articles addressing the topic of tumor modeling from molecular biology, biochemistry, microorganisms, cells and organoids, fishes, animals and xenografts, up to computational cancer models and patient data analysis. This representative eBook describes that there is not a single molecular defined tumor but rather a heterogenic and highly variable complex of different individual diseases. This is what makes research on cancer so difficult, expensive, and explains the broad number of models needed for research. Our authors describe new next-generation sequencing-based methods to analyze complex patterns of chromosomal aberrations in order to understand the molecular biology of tumorigenesis as well as the role of cellular senescence and dormancy in the aetiology of tumor formation and development of therapy resistance of tumors. The current developments on 3D cultures are thoroughly reviewed, as these models help to overcome the current limitations of cell cultures and allow a more accurate mimicry of the native cancer tissue, including cellular heterogeneity and restore specific biochemical and morphological. Reviews about tumor models in zebrafish, different transgenic mouse strains and pigs conclude the book. In the final two chapters of this volume, the authors discuss the theoretical and mathematical models developed in cancer research.