Written in EnglishRead online
Includes bibliographical references and index.
|Statement||editors, Thomas S. Deisboeck and Georgio S. Stamatakos.|
|Series||Chapman and Hall/CRC mathematical & computational biology series -- 34, Chapman and Hall/CRC mathematical & computational biology series -- 34.|
|Contributions||Deisboeck, Thomas S., Stamatakos, Georgio S.|
|LC Classifications||RC267 .T615 2008|
|The Physical Object|
|LC Control Number||2010008845|
Download Multiscale cancer modeling
Mar 23, · Drawing on an interdisciplinary group of distinguished international experts, Multiscale Cancer Modeling discusses the scientific and technical expertise Multiscale cancer modeling book 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.4/5(1). Multiscale Cancer Modeling - CRC Press Book 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.
Multiscale Multiscale cancer modeling book of Cancer: An Integrated Experimental and Mathematical Modeling Approach 1st Edition by Vittorio Cristini (Author)Cited by: INTRODUCTION Cancer growth, and as a particular example in this paper, solid tumor growth, is a complicated phenomenon involving many interrelated processes across a wide range of spatial and temporal scales, and as such presents the mathematical modeler with a correspondingly complex set of problems to solve.
e aim of this paper is to formulate a multiscale mathematical model of solid Cited by: 1. Multiscale Modeling of Cancer An Integrated Experimental and Mathematical Modeling Approach Mathematical modeling, analysis, and simulation are set to play crucial roles in explain- ing tumor behavior and the uncontrolled growth of cancer cells over multiple time and.
Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus.
Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate ekodeniz.com by: Part of the Modeling and Simulation in Science, Engineering and Technology book series (MSSET) Cancer is a complex multiscale disease involving inter-related processes across a wide range of temporal and spatial ekodeniz.com: Gibin Powathil, Mark A.
Chaplain. The types represent stages in the cancer progression. For example, in colon cancer, type 1 cells have one copy of the gene APC inactivated, type 2 Multiscale cancer modeling book have both copies inactivated, type 3. Rick Durrett is a James B. Duke Professor of Mathematics at Duke University in Durham, NC.
The NOOK Book (eBook) of the Multiscale Cancer Modeling by Thomas S. Deisboeck at Barnes & Noble. FREE Shipping on $ or more. Holiday Shipping Membership Educators Gift Cards Stores & Price: $ Although Multiscale Cancer Modeling has a realistic view in the process of tumor growth, its numerical algorithm is time consuming.
Therefore, it is problematic to run and to find the best treatment plan for chemotherapy, even in case of a small size of ekodeniz.com by: 4. Aug 15, · In summary, multiscale cancer modeling is a most promising, innovative research area that constitutes a critical driver for the field of integrative cancer systems ekodeniz.com by: Guiot, P.P.
Delsanto and A.S. Gliozzi --Multi-scale mathematical modelling of vascular tumour growth: an exercise in transatlantic cooperation / Mark A.J. Chaplain [and others] --A multiscale simulation framework for modeling solid tumor growth with an explicit vessel network / S.
Hirsch [and others] --Building stochastic models for cancer. Multiscale Modeling of Cancer: An Integrated Experimental and Mathematical Modeling Approach Hardcover – 9 Sep by Vittorio Cristini, John Lowengrub (Author)Author: Vittorio Cristini, John Lowengrub.
MULTISCALE CANCER MODELING Multiscale cancer modelers already have a wealth of useful, mostly scale-specific resources to refer to or base their innovative work on, but they also face the enormous challenge of developing more realistic and more accurate predictive models. The fundamental reason is that, when considering the increasing number.
Multiscale Cancer Modeling. Multiscale Modeling: A Bayesian Perspective is not really a textbook. It is more like an advanced-level reference book for graduate students and geostatistical researchers interested in learning about the advances in this field.
Sun et al. proposed a novel multiscale, agent-based computational model including both angiogenesis and EGFR modules to investigate the brain cancer response under tyrosine kinase inhibitors (TKIs) treatment.
The angiogenesis module, which was integrated into the agent-based tumor model, consisted of a set of reaction–diffusion equations that explained the spatio-temporal evolution of the distributions Cited by: Jul 26, · A Multiscale, Cell-Based Framework for Modeling Cancer Development.
Computational Science – ICCS() Modeling the effects of Cited by: About this Textbook This book contains lecture notes of current development in multiscale modeling, computations and applications.
It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. This is where multiscale modeling comes in. By considering simultaneously models at diﬀerent scales, we hope to arrive at an approach that shares the eﬃciency of the macro-scopic models as well as the accuracy of the microscopic models.
This idea is far from being new. After all, there has been considerable eﬀorts in trying to understand. Scale ranges. A multiscale cancer ABM attempts to integrate across many spatiotemporal scales (from atomic to molecular, cellular, multicellular, organ, up to multi-organ systems) to provide a more complete and accurate representation of a variety of phenomena including cancer initiation, growth, invasion, and metastasis .We only briefly describe the general methods for modeling cancer Cited by: The multiscale nature of cancer requires modeling approaches that can handle multiple subcellular and cellular aspects acting on different time and space scales.
Hybrid models provide a way to integrate both continuous and discrete variables that are used to denote concentration or density fields and individual cells, respectively [ 1 ].Cited by: Modeling the interactions between compliant microcapsules and patterned surfaces.
Part II, Applications in Biology, covers: Coarse-grained and multiscale simulations of lipid bilayers. Stochastic approach to biochemical kinetics.
In silico modeling of angiogenesis at multiple scales. Mar 21, · Multiscale Simulations and Mechanics of Biological Materials A compilation of recent developments in multiscale simulation and computational biomaterials written by leading specialists in the field Presenting the latest developments in multiscale mechanics and multiscale simulations, and offering a unique viewpoint on multiscale modelling of biological materials, this book outlines the latest.
Sep 15, · Multiscale modeling has now been well-accepted as a powerful tool to quantitatively represent, simulate, understand, and predict cancer progression and development across multiple biological scales.
In this chapter, we focus on a specific type of multiscale cancer models where molecular signaling profiles are explicitly linked to the Author: Zhihui Wang, Vittorio Cristini.
Nov 15, · On the basis of the processes implicated by frequently mutated genes associated with inflammation and cancer in three organs (stomach, colon, and liver) extracted from the Gene Expression Omnibus, The Cancer Genome Atlas, and Gene Ontology databases, we present a multiscale model of the long-term evolutionary dynamics leading from inflammation Cited by: Martin Oliver Steinhauser deals with several aspects of multiscale materials modeling and simulation in applied materials research and fundamental science.
He covers various multiscale modeling approaches for high-performance ceramics, biological bilayer membranes, semi-flexible polymers, and human cancer. In this study, we used a modeling approach to connect cellular mechanisms underlying cancer drug resistance to population-level patient survival.
To predict progression-free survival in cancer patients with metastatic melanoma, we developed a set of stochastic differential equations to describe the dynamics of heterogeneous cell populations Author: Xiaoqiang Sun.
Mar 21, · Multiscale modeling The fields of theoretical and mathematical biology have pioneered the development of mathematical and computational models of biological systems.
Systems biology has contributed workflows for data-driven modeling and model-driven experimentation to the life ekodeniz.com by: Multiscale modeling is becoming essential for accurate, rapid simulation in science and engineering.
This book presents the results of three decades of research on multiscale modeling in process engineering from principles to application, and its generalization for different fields. Multiphysics and Multiscale Modeling: Techniques and Applications emphasizes the use of multiphysics and multiscale techniques to aid in the understanding and development of complex physical behaviors and systems.
This book serves as a resource in mechanical engineering, bioengineering, and materials engineering study, practice, and research. Multiscale modeling of cancer: an integrated experimental and mathematical modeling approach.
[Vittorio Cristini; John Lowengrub] -- "Mathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth. In meteorology, multiscale modeling is the modeling of interaction between weather systems of different spatial and temporal scales that produces the weather that we experience.
The most challenging task is to model the way through which the weather systems interact as models cannot see beyond the limit of the model grid size.
Dec 09, · DOI link for Multiscale Modeling. Multiscale Modeling book. From Atoms to Devices. Multiscale Modeling. DOI link for Multiscale Modeling. Multiscale Modeling book. From Atoms to Devices. Edited By Pedro Derosa, Tahir Cagin. Edition 1st Edition. First Published eBook Published 9 December Cited by: 3.
Multiscale Modeling and Simulation of Composite Materials and Structures presents the state of the art in multiscale modeling and simulation techniques for composite materials and structures. The text focuses on the structural and functional properties of engineering composites and the sustainable high performance of components and structures.
Computational Immunology: Models and Tools. encompasses the methodological framework and application of cutting-edge tools and techniques to study immunological processes at a systems level, along with the concept of multi-scale modeling. The book's emphasis is on selected cases studies and application of the most updated technologies in computational modeling, discussing topics such as.
Sep 01, · Each of these single reports have shown the potential of multi-scale modeling, however a complete multi-scale model of lung cancer is still under development. Overall, multi-scale modeling can have profound contributions toward predicting diagnosis and treatment by revealing synergies and previously unappreciated ekodeniz.com: Olivier Gevaert.
Building upon the ideas introduced in their previous book, Derivatives in Financial Markets with Stochastic Volatility, the authors study the pricing and hedging of financial derivatives under stochastic volatility in equity, interest-rate, and credit ekodeniz.com: Jean-Pierre Fouque, George Papanicolaou, Ronnie Sircar, Knut Sølna.
CISNET Modeling Approach. CISNET's flexible broad-based disease models incorporate a central cancer model, which is modified by the full range of cancer control interventions (i.e., changing risk factor profiles of the population, new screening modalities, and treatment regimens).
Outputs can include the full range of the benefits and costs. The Technologically Integrated Oncosimulator: Combining Multiscale Cancer Modeling With Information Technology in the In Silico Oncology Context Abstract: This paper outlines the major components and function of the technologically integrated oncosimulator developed primarily within the Advancing Clinico Genomic Trials on Cancer (ACGT) ekodeniz.com by: Incorporating continuum mechanics, quantum mechanics, statistical mechanics, atomistic simulations and multiscale techniques, the book explains many of the key theoretical ideas behind multiscale modeling.
Classical topics are blended with new techniques to demonstrate the connections between different fields and highlight current research trends.Jun 21, · Thus, we proposed a novel multi-scale agent-based computational model that integrates the angiogenesis into tumor growth to study the response of melanoma cancer under combined drug treatment.
Our multi-scale agent-based model can simulate the melanoma tumor growth with angiogenesis under combined drug ekodeniz.com by: