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Modelling And Computational Approaches For Multi Scale Phenomena In Cancer Research From Cancer Evolution To Cancer Treatment
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Book Synopsis Modelling and Computational Approaches for Multi-Scale Phenomena in Cancer Research: From Cancer Evolution to Cancer Treatment by : Raluca Eftimie
Download or read book Modelling and Computational Approaches for Multi-Scale Phenomena in Cancer Research: From Cancer Evolution to Cancer Treatment written by Raluca Eftimie and published by World Scientific Publishing Europe Limited. This book was released on 2024-06-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer development and progression is the result of biological phenomena that occur across multiple temporal and spatial scales. Recent years have seen a flurry of multi-scale mathematical models developed to generate and test new biological hypotheses related to cancer development, progression, and various treatment approaches. This led to the development of new computational and analytical approaches aimed at investigating these multiscale models.This review volume summarises some of the current state of the art related to the modelling, experimental investigation and data assimilation for multiscale phenomena during cancer development, evolution and treatment, as well as computational and analytical investigation of the multi-scale models developed to reproduce the biological phenomena. The book also identifies the experimental and theoretical open problems that will have to be addressed in the near future in order to advance this field. Modelling and Computational Approaches for Multi-scale Phenomena in Cancer Research is an excellent resource for both early career and advanced researchers.
Book Synopsis Selected Topics in Cancer Modeling by : Nicola Bellomo
Download or read book Selected Topics in Cancer Modeling written by Nicola Bellomo and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Introduction to Physical Oncology by : Vittorio Cristini
Download or read book An Introduction to Physical Oncology written by Vittorio Cristini and published by CRC Press. This book was released on 2017-06-26 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Physical oncology has the potential to revolutionize cancer research and treatment. The fundamental rationale behind this approach is that physical processes, such as transport mechanisms for drug molecules within tissue and forces exchanged by cancer cells with tissue, may play an equally important role as biological processes in influencing progression and treatment outcome. This book introduces the emerging field of physical oncology to a general audience, with a focus on recent breakthroughs that help in the design and discovery of more effective cancer treatments. It describes how novel mathematical models of physical transport processes incorporate patient tissue and imaging data routinely produced in the clinic to predict the efficacy of many cancer treatment approaches, including chemotherapy and radiation therapy. By helping to identify which therapies would be most beneficial for an individual patient, and quantifying their effects prior to actual implementation in the clinic, physical oncology allows doctors to design treatment regimens customized to each patient’s clinical needs, significantly altering the current clinical approach to cancer treatment and improving the outcomes for patients.
Book Synopsis Multiscale Cancer Modeling by : Thomas S. Deisboeck
Download or read book Multiscale Cancer Modeling written by Thomas S. Deisboeck and published by CRC Press. This book was released on 2010-12-08 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 dat
Book Synopsis Multiscale Modeling of Cancer by : Vittorio Cristini
Download or read book Multiscale Modeling of Cancer written by Vittorio Cristini and published by Cambridge University Press. This book was released on 2010-09-09 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Introduction to Mathematical Oncology by : Yang Kuang
Download or read book Introduction to Mathematical Oncology written by Yang Kuang and published by CRC Press. This book was released on 2018-09-03 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Cancer, Complexity, Computation by : Igor Balaz
Download or read book Cancer, Complexity, Computation written by Igor Balaz and published by Springer Nature. This book was released on 2022-08-11 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents unique compendium of groundbreaking ideas where scientists from many different backgrounds are united in their interest in interdisciplinary approaches towards origins and development of cancers, innovative ways of searching for cancer treatment and the role of cancer in the evolution. Chapters give an unequivocal slice of all areas that relate to a quest for understanding cancer and its origin as many-fold nonlinear system, complexity of the cancer developments, a search for cancer treatment using artificial intelligence and evolutionary optimisation, novel modelling techniques, molecular origin of cancer, the role of cancer in evolution of species, interpretation of cancer in terms of artificial life and artificial immune systems, swarm intelligence, cellular automata, computational systems biology, genetic networks, cellular computing, validation through in vitro/vivo tumour models and tumour on chip devices. The book is an inspiring blend of theoretical and experimental results, concepts and paradigms. Distinctive features The book advances widely popular topics of cancer origin, treatment and understanding of its progress The book is comprised of unique chapters written by world top experts in theoretical and applied oncology, complexity theory, mathematics, computer science. The book illustrates attractive examples of mathematical and computer models and experimental setups.
Book Synopsis Computational Systems Biology Approaches in Cancer Research by : Inna Kuperstein
Download or read book Computational Systems Biology Approaches in Cancer Research written by Inna Kuperstein and published by CRC Press. This book was released on 2019-09-09 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty." — Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." — Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications’
Book Synopsis Mathematical Methods for Cancer Evolution by : Takashi Suzuki
Download or read book Mathematical Methods for Cancer Evolution written by Takashi Suzuki and published by Springer. This book was released on 2017-06-13 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this monograph is to describe recent developments in mathematical modeling and mathematical analysis of certain problems arising from cell biology. Cancer cells and their growth via several stages are of particular interest. To describe these events, multi-scale models are applied, involving continuously distributed environment variables and several components related to particles. Hybrid simulations are also carried out, using discretization of environment variables and the Monte Carlo method for the principal particle variables. Rigorous mathematical foundations are the bases of these tools.The monograph is composed of four chapters. The first three chapters are concerned with modeling, while the last one is devoted to mathematical analysis. The first chapter deals with molecular dynamics occurring at the early stage of cancer invasion. A pathway network model based on a biological scenario is constructed, and then its mathematical structures are determined. In the second chapter mathematical modeling is introduced, overviewing several biological insights, using partial differential equations. Transport and gradient are the main factors, and several models are introduced including the Keller‒Segel systems. The third chapter treats the method of averaging to model the movement of particles, based on mean field theories, employing deterministic and stochastic approaches. Then appropriate parameters for stochastic simulations are examined. The segment model is finally proposed as an application. In the fourth chapter, thermodynamic features of these models and how these structures are applied in mathematical analysis are examined, that is, negative chemotaxis, parabolic systems with non-local term accounting for chemical reactions, mass-conservative reaction-diffusion systems, and competitive systems of chemotaxis. The monograph concludes with the method of the weak scaling limit applied to the Smoluchowski‒Poisson equation.
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by Springer Nature. This book was released on 2021-12-11 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Symposium on Mathematical and Computational Oncology, ISMCO 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 3 full papers and 4 short papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; spatio-temporal tumor modeling and simulation; general cancer computational biology; mathematical modeling for cancer research; computational methods for anticancer drug development.
Book Synopsis Modeling Tumor Vasculature by : Trachette L. Jackson
Download or read book Modeling Tumor Vasculature written by Trachette L. Jackson and published by Springer Science & Business Media. This book was released on 2011-11-23 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: To profoundly understand biology and harness its intricacies for human benefit and the mitigation of human harm requires cross-disciplinary approaches that incorporate sophisticated computational and mathematical modeling techniques. These integrative strategies are essential to achieve rapid and significant progress in issues, in health and disease, which span molecular, cellular and tissue levels. The use of mathematical models to describe various aspects of tumor growth has a very long history, dating back over six decades. Recently, however, experimental and computational advances have improved our in the understanding of how processes act at multiple scales to mediate the development of tumor vasculature and drive the advancement of cancer. This book will showcase the development and utilization of new computational and mathematical approaches to address multiscale challenges associated with tumor vascular development. In Part I: Cell Signaling and Molecular Aspects of Tumor Blood Vessel Formation, it will be come clear that mathematical modeling can help to biochemically and biomechanically phenotype one of the most important cell types involved in cancer progression: vascular endothelial cells. When subverted by the tumor modulated environment, vascular endothelial cells form a new vascular supply capable of nourishing and translocating cancer cells to other tissues. The models in Part I illustrate the importance of quantitative approaches for gaining a deeper understanding of how normal and abnormal aspects of signal integration culminate in the cell proliferation, migration, and survival decisions that result in pathological tumor angiogenesis. The focus of Part II is the angiogenesis cascade and all of its complexities. Successful angiogenesis is mediated by the intricate interplay between biochemical and biomechanical mechanisms, including cell-cell and cell-matrix interactions, cell surface receptor binding, and intracellular signal transduction. A major challenge facing the cancer research community is to integrate known information in a way that improves our understanding of the principal underpinnings driving tumor angiogenesis and that will advance efforts aimed at the development of new therapies for treating cancer. The chapters in Part II will highlight several mathematical and computational approaches for that can potentially address this challenge. While the first two thirds of the book’s chapters demonstrate how important insights can be gained by studying cell signaling and vascular morphology and function, the series of chapters in Part III: Whole Organ Modeling of Tumor Growth and Vasculature, will integrate vasculature development with tumor growth dynamics. These two processes strongly depend on one another in ways that can only be theoretically investigated by biophysical approaches that cut across several levels of biological organization and describe both the tumor and the developing vasculature as they co-evolve. The purpose of this edited volume is not to provide a comprehensive review of all modeling efforts that address tumor vascular modeling; instead, a variety of interesting and innovative mathematical modeling approaches for understanding the development and effects of tumor vasculature are highlighted in order to illustrate some of the emerging trends in the field.
Book Synopsis Multiscale Modeling of Tissue Growth for Cancer Prognosis by : Mohammad Mamunur Rahman
Download or read book Multiscale Modeling of Tissue Growth for Cancer Prognosis written by Mohammad Mamunur Rahman and published by . This book was released on 2016 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is a major life threatening disease in the world. With the advancement of computational mathematics, big data science and unprecedented computational power, it becomes possible to investigate the complex multiscale growth phenomenon of the tumor for cancer prognosis to provide pre-operative treatment planning and predict treatment outcome using mathematical modeling and computer simulation. The growth of biological tissue is a complex process because it involves various biophysically- and biochemically-induced events at different spatial and temporal scales. Multiscale modeling techniques allow us to incorporate important features at multiple scales to examine the tissue growth mechanism and determine the major factors affecting the growth process. The primary objective of this doctoral research is to develop a multiscale modeling framework for the growth of biological tissue and apply to tumor growth and cancer prognosis. Another objective of this study is to understand the effect of anticancer drugs on cancer cell growth, cell proliferation, and overall tumor size. The multiscale framework consists of a tissue scale model, a cellular activity and growth model and a subcellular signaling pathway model. To predict the tissue growth in the macroscopic (tissue) scale, a continuum model is constructed where the biological tissue is represented as a mixture of multiple constituents. Each of such constituents, in their solid, liquid or gas phase, are represented by either a volume fraction or concentration. The constituents interact with each other through mass and momentum exchange. The governing equations are developed based on both mass and momentum conservation laws. The constitutive equations account for tissue anisotropy, nonlinear behavior, and thermodynamic consistency. The system of partial differential equations are solved using finite element techniques. To bridge the spatial scales, each finite element is further discretized into finer cell clusters of different kinds to represent various biological cellular states at the microscopic scale to model cellular growth and proliferation by using an agent-based model to determine various activities at the cellular scale such as the cell division, cell death, phenotypical alteration, etc. The cellular scale events are also broken down and discretized temporally to model the effects of a subcellular signaling pathway (e.g. PI3K/AKT/mTOR pathway, also known as mTOR pathway) on the cellular and tissue scales. In many cancers, mTOR pathway becomes hyperactive and promotes abnormal cell proliferation. The mechanism and effects of an mTOR inhibiting drug known as rapamycin (e.g., eRapa) are tested using in silico methods. These subcellular activities are modeled using a set of ordinary differential equations. A statistical inverse algorithm is used for model calibration and validation. The Bayesian inference method accounts for the uncertainties of the model parameters, which are calibrated with the experimental observations. Generally speaking, the multiscale modeling framework presented in this dissertation may provide better understanding of the tissue growth process by providing insight on the effects of various factors at different spatiotemporal scales. It can also be potentially used to construct patient-specific tissue growth models for in silico drug testing, treatment planning, and prognosis.
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by Springer Nature. This book was released on 2020-12-07 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Symposium on Mathematical and Computational Oncology, ISMCO 2020, which was supposed to be held in San Diego, CA, USA, in October 2020, but was instead held virtually due to the COVID-19 pandemic. The 6 full papers and 4 short papers presented together with 1 invited talk were carefully reviewed and selected from 28 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; general cancer computational biology; and posters.
Book Synopsis A Guide to Outcome Modeling In Radiotherapy and Oncology by : Issam El Naqa
Download or read book A Guide to Outcome Modeling In Radiotherapy and Oncology written by Issam El Naqa and published by CRC Press. This book was released on 2018-04-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life. It contains coverage of the relevant data sources available for model construction (panomics), ranging from clinical or preclinical resources to basic patient and treatment characteristics, medical imaging (radiomics), and molecular biological markers such as those involved in genomics, proteomics and metabolomics. It also includes discussions on the varying methodologies for predictive model building with analytical and data-driven approaches. This book is primarily intended to act as a tutorial for newcomers to the field of outcome modeling, as it includes in-depth how-to recipes on modeling artistry while providing sufficient instruction on how such models can approximate the physical and biological realities of clinical treatment. The book will also be of value to seasoned practitioners as a reference on the varying aspects of outcome modeling and their current applications. Features: Covers top-down approaches applying statistical, machine learning, and big data analytics and bottom-up approaches using first principles and multi-scale techniques, including numerical simulations based on Monte Carlo and automata techniques Provides an overview of the available software tools and resources for outcome model development and evaluation, and includes hands-on detailed examples throughout Presents a diverse selection of the common applications of outcome modeling in a wide variety of areas: treatment planning in radiotherapy, chemotherapy and immunotherapy, utility-based and biomarker applications, particle therapy modeling, oncological surgery, and the design of adaptive and SMART clinical trials
Book Synopsis Computational Biology of Cancer by : Dominik Wodarz
Download or read book Computational Biology of Cancer written by Dominik Wodarz and published by World Scientific. This book was released on 2005 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Provides an introduction to computational methods in cancer biology - Follows a multi-disciplinary approach
Book Synopsis Multiscale Models in Mechano and Tumor Biology by : Alf Gerisch
Download or read book Multiscale Models in Mechano and Tumor Biology written by Alf Gerisch and published by Springer. This book was released on 2018-03-16 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents and discusses the state of the art and future perspectives in mathematical modeling and homogenization techniques with the focus on addressing key physiological issues in the context of multiphase healthy and malignant biological materials. The highly interdisciplinary content brings together contributions from scientists with complementary areas of expertise, such as pure and applied mathematicians, engineers, and biophysicists. The book also features the lecture notes from a half-day introductory course on asymptotic homogenization. These notes are suitable for undergraduate mathematics or physics students, while the other chapters are aimed at graduate students and researchers.
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by Springer Nature. This book was released on 2019-11-14 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Symposium on Mathematical and Computational Oncology, ISMCO'2019, held in Lake Tahoe, NV, USA, in October 2019. The 7 full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections named: Tumor evolvability and intra-tumor heterogeneity; Imaging and scientific visualization for cancer research; Statistical methods and data mining for cancer research (SMDM); Spatio-temporal tumor modeling and simulation (STTMS).
