Bioinformatics in Human Health and Heredity, Vol 28. Handbook of Statistics

  • ID: 2088890
  • Book
  • 612 Pages
  • Elsevier Science and Technology
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The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.

The Handbook of Statistics, a series of self-contained reference books. Each volume is devoted to a particular topic in statistics with Volume 28 dealing with bioinformatics. Every chapter is written by prominent workers in the area to which the volume is devoted. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience.

  • Comprehensively presents the various aspects of statistical methodology
  • Discusses a wide variety of diverse applications and recent developments
  • Contributors are internationally renowned experts in their respective areas
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Chapter 1: Introduction: Wither Bioinformatics in Human Health and Heredity Section A: Microarray Analysis Chapter 2: Hierarchical Bayesian Methods for Microarray Data Chapter 3: Statistical Analysis of Time-Course and Dose-Response Microarray Experiments Chapter 4: Meta-analysis of High Throughput Oncology Data Section B: Analytical Methods Chapter 5: A Statistical Appraisal of Biomarker Selection Methods Applicable to HIV/AIDS Research Chapter 6: The use of Hamming Distance in Bioinformatics Chapter 7: Asymptotic Expansion of the Distributions of the Least Squares Estimators in Factor Analysis and Structural Equation Modeling Chapter 8: Multiple Testing and False Discovery Rate Issues in Bioinformatics Section C: Genetics and DNA Forensics Chapter 9: Applications of Bayesian Neural Networks in Prostate Cancer Study Chapter 10: Statistical Methods for Detecting Functional Divergence of Gene Families Chapter 11: Sequence Pattern Discovery with Applications to Understanding Gene Regulation and Vaccine Design Chapter 12: Single-locus Association Tests by Ordered Statistics Chapter 13: A Molecular Information Method to Estimate Population Admixture Chapter 14: Effects of Inclusion of Relatives in DNA Databases: Empirical Observations from 13K SNPs in Hap-Map Population Data Section D: Epidemiology Chapter 15: Measurement and Analysis of Quality of Life in Epidemiology Chapter 16: Quality of Life Perspectives in Chronic Disease and Disorder Studies Chapter 17: Bioinformatics of Obesity Chapter 18: Exploring Genetic Epidemiology Data with Bayesian Networks Section E: Database Issues Chapter 19: Perturbation Methods for Protecting Numerical Data: Evolution and Evaluation Chapter 20: Protecting Data Confidentiality in Public Release Datasets: Approaches Based on Multiple Imputation

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Rao, C.R.
C. R. Rao, born in India is one of this century's foremost statisticians, received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. Rao is currently at Penn State as Eberly Professor of Statistics and Director of the Center for Multivariate Analysis. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering.

Chakraborty, Ranajit.

Sen, Pranab K.
Pranab K. Sen is Cary C. Boshamer Professor of Biostatistics and Statistics at the University of North Carolina, and is a Fellow of the Institute of Mathematical Statistics and of the American Statistical Association. He is also an elected member of the International Statistical Institute.Prenab K. Sen is author or co-author of multiple volumes in Mathematical Statistics, Probability Theory and Biostatistics, and has published extensively in nonparametrics, multivariate and sequential analysis, and reliability and survival analysis.
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