Описание: Chapter 1. Stochastic Models of Cell Proliferation Kinetics based on Branching Processes.- Chapter 2. Age-Dependent Branching Processes with Non-Homogeneous Poisson Immigration as Models of Cell Kinetics.- Chapter 3. A Study of the Correlation Structure of Microarray Gene Expression Data Based on Mechanistic Modeling of Cell Population Kinetics.- Chapter 4. Correlation Between the True and False Discoveries in a Positively Dependent Multiple Comparison Problem.- Chapter 5. Multiple Testing Procedures: Monotonicity and Some of Its Implications.- Chapter 6. Applications of Sequential Methods in Multiple Hypothesis Testing.- Chapter 7. Multistage Carcinogenesis: A Unified Framework for Cancer Data Analysis.- Chapter 8. A Machine-Learning Algorithm for Estimating and Ranking the Impact of Environmental Risk Factors in Exploratory Epidemiological Studies.- Chapter 9. A Latent Time Distribution Model for the Analysis of Tumor Recurrence Data: Application to the Role of Age in Breast Cancer.- Chapter 10. Estimation of Mean Residual Life.- Chapter 11. Likelihood Transformations and Artificial Mixtures.- Chapter 12. On the Application of Flexible Designs when Searching for the Better of Two Anticancer Treatments.- Chapter 13. Parameter Estimation for Multivariate Nonlinear Stochastic Differential Equation Models: A Comparison Study.- Chapter 14. On Frailties, Archimedean Copulas and Semi-Invariance Under Truncation.- Chapter 15. The Generalized ANOVA - A Classic Song Sung with Modern Lyrics.- Chapter 16. Analyzing Gene Pathways from Microarrays to Sequencing Platforms.- Chapter 17. A New Approach for Quantifying Uncertainty in Epidemiology.- Chapter 18. Branching Processes: A Personal Historical Perspective.- Chapter 19. Principles of Mathematical Modeling in Biomedical Sciences: An Unwritten Gospel of Andrei Yakovlev.
Автор: B.I. Grudinko; Andrej Yu. Yakovlev; Nikolaj M. Yan Название: Transient Processes in Cell Proliferation Kinetics ISBN: 3540518312 ISBN-13(EAN): 9783540518310 Издательство: Springer Рейтинг: Цена: 10976.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A mathematician who has taken the romantic decision to devote himself to biology will doubtlessly look upon cell kinetics as the most simple and natural field of application for his knowledge and skills.
Автор: Prentice Название: The Statistical Analysis Of Multiva ISBN: 1482256576 ISBN-13(EAN): 9781482256574 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. Much of the literature on the analysis of censored correlated failure time data uses frailty or copula models to allow for residual dependencies among failure times, given covariates. In contrast, this book provides a detailed account of recently developed methods for the simultaneous estimation of marginal single and dual outcome hazard rate regression parameters, with emphasis on multiplicative (Cox) models. Illustrations are provided of the utility of these methods using Women’s Health Initiative randomized controlled trial data of menopausal hormones and of a low-fat dietary pattern intervention. As byproducts, these methods provide flexible semiparametric estimators of pairwise bivariate survivor functions at specified covariate histories, as well as semiparametric estimators of cross ratio and concordance functions given covariates. The presentation also describes how these innovative methods may extend to handle issues of dependent censorship, missing and mismeasured covariates, and joint modeling of failure times and covariates, setting the stage for additional theoretical and applied developments. This book extends and continues the style of the classic Statistical Analysis of Failure Time Data by Kalbfleisch and Prentice. Ross L. Prentice is Professor of Biostatistics at the Fred Hutchinson Cancer Research Center and University of Washington in Seattle, Washington. He is the recipient of COPSS Presidents and Fisher awards, the AACR Epidemiology/Prevention and Team Science awards, and is a member of the National Academy of Medicine. Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina.
Описание: What every neuroscientist should know about the mathematical modeling of excitable cells. Combining empirical physiology and nonlinear dynamics, this text provides an introduction to the simulation and modeling of dynamic phenomena in cell biology and neuroscience. It introduces mathematical modeling techniques alongside cellular electrophysiology. Topics include membrane transport and diffusion, the biophysics of excitable membranes, the gating of voltage and ligand-gated ion channels, intracellular calcium signalling, and electrical bursting in neurons and other excitable cell types. It introduces mathematical modeling techniques such as ordinary differential equations, phase plane, and bifurcation analysis of single-compartment neuron models. With analytical and computational problem sets, this book is suitable for life sciences majors, in biology to neuroscience, with one year of calculus, as well as graduate students looking for a primer on membrane excitability and calcium signalling.
Автор: Manly, Bryan F.J. , Navarro Alberto, Jorge A. Название: Randomization, Bootstrap and Monte Carlo Methods in Biology ISBN: 0367512874 ISBN-13(EAN): 9780367512873 Издательство: Taylor&Francis Рейтинг: Цена: 7961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The fourth edition of the book illustrates a large number of statistical methods with an emphasis on biological applications. It provides comprehensive coverage of computer-intensive applications, with datasets available online.
Автор: Manly, Bryan F.J. , Navarro Alberto, Jorge A. Название: Randomization, Bootstrap and Monte Carlo Methods in Biology ISBN: 0367349949 ISBN-13(EAN): 9780367349943 Издательство: Taylor&Francis Рейтинг: Цена: 21437.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The fourth edition of the book illustrates a large number of statistical methods with an emphasis on biological applications. It provides comprehensive coverage of computer-intensive applications, with datasets available online.
Автор: Ravishanker Название: First Course In Linear Model Theory ISBN: 1439858055 ISBN-13(EAN): 9781439858059 Издательство: Taylor&Francis Рейтинг: Цена: 14545.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition features several new topics that are extremely relevant to the current research in statistical methodology. Revised or expanded topics include analysis of covariance, Bayesian linear and generalized linear model, nonlinear regression, among others.
Автор: Kaltenbach Hans-Michael Название: Statistical Design and Analysis of Biological Experiments ISBN: 303069643X ISBN-13(EAN): 9783030696436 Издательство: Springer Рейтинг: Цена: 10366.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research.
Автор: Hothorn Название: A Handbook of Statistical Analyses using R, Third Edition ISBN: 1482204584 ISBN-13(EAN): 9781482204582 Издательство: Taylor&Francis Рейтинг: Цена: 11023.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.
New to the Third Edition
Three new chapters on quantile regression, missing values, and Bayesian inference
Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables
Additional exercises
More detailed explanations of R code
New section in each chapter summarizing the results of the analyses
Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses
Whether you're a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.
Автор: M. L?ssig; A. Valleriani Название: Biological Evolution and Statistical Physics ISBN: 3642077439 ISBN-13(EAN): 9783642077432 Издательство: Springer Рейтинг: Цена: 13677.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This set of lecture notes gives a first coherent account of a novel aspect of the living world that can be called biological information.
Автор: Desu, M.M. , Raghavarao, D. Название: Nonparametric Statistical Methods For Complete and Censored Data ISBN: 0367394952 ISBN-13(EAN): 9780367394950 Издательство: Taylor&Francis Рейтинг: Цена: 10411.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Balancing the "cookbook" approach of some texts with the more mathematical approach of others, Nonparametric Statistical Methods for Complete and Censored Data introduces commonly used non-parametric methods for complete data and extends those methods to right censored data analysis. Whenever possible, the authors derive their methodology from the general theory of statistical inference and introduce the concepts intuitively for students with minimal backgrounds. Derivations and mathematical details are relegated to appendices at the end of each chapter, which allows students to easily proceed through each chapter without becoming bogged down in a lot of mathematics.
In addition to the nonparametric methods for analyzing complete and censored data, the book covers optimal linear rank statistics, clinical equivalence, analysis of block designs, and precedence tests. To make the material more accessible and practical, the authors use SAS programs to illustrate the various methods included.
Exercises in each chapter, SAS code, and a clear, accessible presentation make this an outstanding text for a one-semester senior or graduate-level course in nonparametric statistics for students in a variety of disciplines, from statistics and biostatistics to business, psychology, and the social scientists.
Prerequisites: Students will need a solid background in calculus and a two-semester course in mathematical statistics.
Описание: This richly illustrated book presents the objectives of, and the latest techniques for, the identifiability analysis and standard and robust regression analysis of complex dynamical models.
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