Statistical Modeling for Biological Systems : In Memory of Andrei Yakovlev. 1st ed. 2020

種類:

電子ブック

責任表示:

edited by Anthony Almudevar, David Oakes, Jack Hall

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

著者名:

• Almudevar, Anthony.
• Oakes, David.
• Hall, Jack.
• SpringerLink (Online service)

ISBN:

9783030346751 [3030346757]    

注記:

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. Es
This book commemorates the scientific contributions of distinguished statistician, Andrei Yakovlev. It reflects upon Dr. Yakovlev’s many research interests including stochastic modeling and the analysis of micro-array data and throughout the book it emphasizes applications of the theory in biology, medicine and public health. The contributions to this volume are divided into two parts. Part A consists of original research articles, which can be roughly grouped into four thematic areas, (i) branching processes, especially as models for cell kinetics, (ii) multiple testing issues as they arise in the analysis of biologic data, (iii) applications of mathematical models and of new inferential techniques in epidemiology, and (iv) contributions to statistical methodology, with an emphasis on the modeling and analysis of survival time data. Part B consists of methodological research reported as a short communication, ending with some personal reflections on research fields associated with Andrei and on his approach

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