Handbook of Statistics: Bioinformatics in Human Health and Heredity

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Overview

The field of statistics not only affects all areas of scientific activity, but also many other matters such aspublic 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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Product Details

  • ISBN-13: 9780444518750
  • Publisher: Elsevier Science
  • Publication date: 10/17/2012
  • Series: Handbook of Statistics Series , #28
  • Pages: 612
  • Product dimensions: 6.10 (w) x 9.10 (h) x 1.10 (d)

Meet the Author

C. R. Rao, born in India, is one of this century's foremost statisticians, and received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. He is Emeritus Holder of the Eberly Family Chair in Statistics at Penn State and Director of the Center for Multivariate Analysis. He has long been recognized as one of the world's top statisticians, and has been awarded 34 honorary doctorates from universities in 19 countries spanning 6 continents. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering.

In 2011 he was recipient of the Royal Statistical Society's Guy Medal in Gold which is awarded triennially to those "who are judged to have merited a signal mark of distinction by reason of their innovative contributions to the theory or application of statistics". It can be awarded both to fellows (members) of the Society and to non-fellows. Since its inception 120 years ago the Gold Medal has been awarded to 34 distinguished statisticians. The first medal was awarded to Charles Booth in 1892. Only two statisticians, H. Cramer (Norwegian) and J. Neyman (Polish), outside Great Britain were awarded the Gold medal and C. R. Rao is the first non-European and non-American to receive the award.

Other awards he has received are the Gold Medal of Calcutta University, Wilks Medal of the American Statistical Association, Wilks Army Medal, Guy Medal in Silver of the Royal Statistical Society (UK), Megnadh Saha Medal and Srinivasa Ramanujan Medal of the Indian National Science Academy, J.C.Bose Gold Medal of Bose Institute and Mahalanobis Centenary Gold Medal of the Indian Science Congress, the Bhatnagar award of the Council of Scientific and Industrial Research, India and the Government of India honored him with the second highest civilian award, Padma Vibhushan, for “outstanding contributions to Science and Engineering / Statistics”, and also instituted a cash award in honor of C R Rao, “to be given once in two years to a young statistician for work done during the preceding 3 years in any field of statistics”.

For his outstanding achievements Rao has been honored with the establishment of an institute named after him, C.R.Rao Advanced Institute for Mathematics, Statistics and Computer Science, in the campus of the University of Hyderabad, India.

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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Table of Contents

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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