Download or read book Applications of Stochastic Models for the Analysis of the Mechanisms of Carcinogenesis written by and published by . This book was released on 1964 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Stochastic Model for Immunological Feedback in Carcinogenesis written by Neil Dubin and published by . This book was released on 1976 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Models for Carcinogenesis written by Wai-Yuan Tan and published by CRC Press. This book was released on 2020-01-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date survey of mathematical models of carcinogenesis, providing the most recent findings of cancer biology as evidence of the models, as well as extensive bibliographies of cancer biology and in-depth mathematical analyses for each of the models. May be used as a reference for biostaticians, biometricians, mathematical and molecular biologists, applied mathematicians, oncologists, cancer and toxicology researchers, environmental scientists, and graduate students in these fields.
Download or read book Stochastic Models Of Tumor Latency And Their Biostatistical Applications written by Alexander D Tsodikov and published by World Scientific. This book was released on 1996-03-20 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph discusses newly developed mathematical models and methods that provide biologically meaningful inferences from data on cancer latency produced by follow-up and discrete surveillance studies. Methods for designing optimal strategies of cancer surveillance are systematically presented for the first time in this book. It offers new approaches to the stochastic description of tumor latency, employs biologically-based models for making statistical inference from data on tumor recurrence and also discusses methods of statistical analysis of data resulting from discrete surveillance strategies. It also offers insight into the role of prognostic factors based on the interpretation of their effects in terms of parameters endowed with biological meaning, as well as methods for designing optimal schedules of cancer screening and surveillance. Last but not least, it discusses survival models allowing for cure rates and the choice of optimal treatment based on covariate information, and presents numerous examples of real data analysis.
Download or read book Handbook of Cancer Models with Applications written by W. Y. Tan and published by World Scientific. This book was released on 2008 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Stochastic Models with Applications to Genetics Cancers AIDS and Other Biomedical Systems written by W. Y. Tan and published by World Scientific. This book was released on 2002 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are applied to many problems in genetics, carcinogenesis, AIDS epidemiology and other biomedical systems.One feature of the book is that it describes the basic MCMC (Markov chain and Monte Carlo) procedures and illustrates how to use the Gibbs sampling method and the multilevel Gibbs sampling method to solve many problems in genetics, carcinogenesis, AIDS and other biomedical systems.As another feature, the book develops many state space models for many genetic problems, carcinogenesis, AIDS epidemiology and HIV pathogenesis. It shows in detail how to use the multilevel Gibbs sampling method to estimate (or predict) simultaneously the state variables and the unknown parameters in cancer chemotherapy, carcinogenesis, AIDS epidemiology and HIV pathogenesis. As a matter of fact, this book is the first to develop many state space models for many genetic problems, carcinogenesis and other biomedical problems.
Download or read book A Stochastic Model for Immunological Feedback in Carcinogenesis written by Neil Dubin and published by Springer Verlag. This book was released on 1976 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling of Cancer Genesis and Prevention written by Nicolae Voiculetz and published by CRC Press. This book was released on 1991-02-26 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review of the interaction between cancer research and mathematical methods for both investigators in the field and newcomers just entering it. The book's primary focus is on the use of computer-assisted mathematical modeling in carcinogenesis and cancer prevention. The first two chapters include a general presentation of the carcinogenesis and anticarcinogenesis molecular mechanisms, followed by a discussion of mathematical models of triggers for gene regulation. A description of the prediction of both carcinogenicity and mutagenicity using quantum mechanical, topological or physico-chemical indices is presented, as well as a discussion of the QSAR analysis of carcinogenesis-inhibiting compounds (known as blocking or suppressive agents).
Download or read book A Stochastic Model for Carcinogenesis with Special Applications to the Initiation and Promotion Phenomena written by Maria Teresa C. Gastardo and published by . This book was released on 1984 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Some Stochastic Models and Data Analysis of Animal Carcinogenicity written by Hongyuan Zhang and published by . This book was released on 1996 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Issues in Risk Assessment written by National Research Council and published by National Academies Press. This book was released on 1993-02-01 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scientific basis, inference assumptions, regulatory uses, and research needs in risk assessment are considered in this two-part volume. The first part, Use of Maximum Tolerated Dose in Animal Bioassays for Carcinogenicity, focuses on whether the maximum tolerated dose should continue to be used in carcinogenesis bioassays. The committee considers several options for modifying current bioassay procedures. The second part, Two-Stage Models of Carcinogenesis, stems from efforts to identify improved means of cancer risk assessment that have resulted in the development of a mathematical dose-response model based on a paradigm for the biologic phenomena thought to be associated with carcinogenesis.
Download or read book Stochastic Modeling of Cellular Cooperation written by Erin Nicole Urwin and published by . This book was released on 2010 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cooperation in biology is a well-known enigma. It is in an individual cell's best interest to behave selfishly, but it is in a collection of cells' best interest if each cell cooperates. We explore aspects of cooperative behavior in the context of cellular systems. We concentrate on spatial aspects of cooperation and study how spatial restrictions effect colony survival. We examine three stochastic models through numerical simulation along with analytic methods. In our first model, we explore the impact of cheaters on a cooperative network of cells. We observe that strict spatial constraints impede harmful effects of cheaters. We note that a similar result was previously observed, by M. Nowak et al, albeit in a different system [13, 12]. We explored an application of our modeling approach to cooperating yeast specifically engineered to demonstrate effects of cooperation [14]. We explored the effects of the presence of cheaters in such a system and found that the viability of colonies depended non-monotonically on the ability of cells to cooperate. This suggests an avenue for further biological experiments. In our last model, we explore cooperative aspects of evolution. We ask the question, "is it more advantageous for cells to acquire each mutation sequentially or to have different cells acquire different mutations and then have them cooperate?" Traditional multi-stage carcinogenesis models depict cancer evolving as a sequence of mutations within each cell. A possible advantage to this evolutionary strategy is that cells are self-sufficient. Possible disadvantageous are that mutations take a long time to occur, and so evolution is very slow. If cells achieve different mutations and then cooperate to form a cancerous phenotype, then they are able to evolve faster. However, they are reliant on others. If one cell type is lost, the whole colony could suffer and so the colony is more prone to stochastic extinction. We found that cooperation speeds up evolution significantly. We also found that the presence of cheaters speeds up evolution even more. This result was surprising because in other contexts cheaters decrease the longevity of a colony.
Download or read book Stochastic and State Space Models of Carcinogenesis with Applications written by Lijun Zhang and published by . This book was released on 2008 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A stochastic model for immunological feedback in carcinogenesis written by Neil Bubin and published by . This book was released on 1976 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic and State Space Models of Carcinogenesis Under Complex Situation written by Xiaowei Yan and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With more and more biological mechanisms of cancer development being discovered, in order to improve cancer control and prevention, it becomes necessary to develop effective and efficient mathematical and statistical models and methods to incorporate the biological information, and to identify critical events in the process of carcinogenesis. In this dissertation, the complex nature of carcinogenesis has been represented by stochastic system model; combining this model with information from observations and prior knowledge, we have developed state space models to evaluate cancer gene mutations and cell proliferation at different cancer development stages. Also, we have proposed a generalized Bayesian method via multi-level Gibbs sampling procedure to predict state (stage) variables of the models. In this dissertation, stochastic models have been proposed for initiation, promotion and complete carcinomas experiments; these experiments are most commonly performed in cancer risk assessment of environmental agents. These stochastic models are simple multi-pathway models which are constructed based on biological mechanisms. The estimates we obtained from the models have provided quantitative evaluation of dose related mutation rates of major genes and cells proliferation rates; these results could be used to assess the risk of developing malignant tumor in the environment we live. More complicated stochastic and state space models have been developed for sporadic human colon cancer and for hereditary and non-hereditary human liver cancer. We have utilized the proposed models to fit to Surveillance Epidemiology and End Results (SEER) data. The results imply that our models have effectively incorporated biological information and observations; these models fitted the data very well and the inferences based on estimate were very consistent with biological findings. Furthermore, the models reflected the complex nature of carcinogenesis. We notice that many cancers are developed through multiple-stage multiple-pathway. Our analyses of colon cancer and liver cancer have showed that some pathways are more devastated than others. This suggests thus it would be more efficient to intervene or treat the critical events in the more devastated pathways. .
Download or read book Stochastic Modeling and Analysis of Pathway Regulation and Dynamics written by Chen Zhao and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: To effectively understand and treat complex diseases such as cancer, mathematical and statistical modeling is essential if one wants to represent and characterize the interactions among the different regulatory components that govern the underlying decision making process. Like in any other complex decision making networks, the regulatory power is not evenly distributed among its individual members, but rather concentrated in a few high power "commanders". In biology, such commanders are usually called masters or canalizing genes. Characterizing and detecting such genes are thus highly valuable for the treatment of cancer. Chapter II is devoted to this task, where we present a Bayesian framework to model pathway interactions and then study the behavior of master genes and canalizing genes. We also propose a hypothesis testing procedure to detect a "cut" in pathways, which is useful for discerning drugs' therapeutic effect. In Chapter III, we shift our focus to the understanding of the mechanisms of action (MOA) of cancer drugs. For a new drug, the correct understanding of its MOA is a key step for its application to cancer treatments. Using the Green Fluorescent Protein technology, researchers have been able to track various reporter genes from the same cell population for an extended period of time. Such dynamic gene expression data forms the basis for drug similarity comparisons. In Chapter III, we design an algorithm that can identify mechanistic similarities in drug responses, which leads to the characterization of their respective MOAs. Finally, in the course of drug MOA study, we observe that cells in a hypothetical homogeneous population do not respond to drug treatments in a uniform and synchronous way. Instead, each cell makes a large shift in its gene expression level independently and asynchronously from the others. Hence, to systematically study such behavior, we propose a mathematical model that describes the gene expression dynamics for a population of cells after drug treatments. The application of this model to dose response data provides us new insights of the dosing effects. Furthermore, the model is capable of generating useful hypotheses for future experimental design.
Download or read book Comparative Oncology written by Alecsandru Ioan Baba and published by . This book was released on 2007 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt:
