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Bioinformatics in Human Health and Heredity - 1st Edition - ISBN: 9780444518750, 9780080930985

Bioinformatics in Human Health and Heredity, Volume 28

1st Edition

Series Volume Editors: C.R. Rao Ranajit Chakraborty Pranab Sen
Hardcover ISBN: 9780444518750
eBook ISBN: 9780080930985
Imprint: North Holland
Published Date: 30th August 2012
Page Count: 612
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Table of Contents

Editorial Board



Introduction: Wither Bioinformatics in Human Health and Heredity

1 Introduction

2 Sciences dealing with biological information and rationale of their integration

3 Goals and major research areas of bioinformatics

4 Why bioinformatics is so important and open areas of research

Bayesian Methods for Microarray Data

1 Introduction

2 Literature review

3 Hierarchical models for microarray analysis

4 Embryonic maize tissue development

5 Conclusion

6 Appendix

Statistical Analysis of Gene Expression Studies with Ordered Experimental Conditions

1 Introduction

2 “Short-series” time-course data

3 “Long series” time-course data for cyclic and developmental processes

4 Concluding remarks

Meta-Analysis of High Throughput Oncology Data

1 Introduction

2 Bayesian Networks

3 Example application in genetic epidemiology

4 Software and applications

5 Summary and future directions

A Statistical Appraisal of Biomarker Selection Methods Applicable to HIV/AIDS Research

1 Introduction

2 Biomarker definitions

3 HIV infection biomarker review

4 Statistical screening methods for biomarker selection

5 Causal inference approaches for biomarker selection

6 Targeted maximum likelihood estimation

7 Classifier performance assessed by ROC curve

8 Some impending statistical challenges

9 Multiplicity considerations in biomarker research

10 An application: hormonal contraception and HIV genital shedding and disease progression (GS study)

11 Discussion and conclusion

The Use of Hamming Distance in Bioinformatics

1 Introduction

2 Some diversity measures

3 U-statistics representation for the Hamming distance based measures in bioinformatics

4 Analysis of variance tests based on Hamming distances

5 MANOVA: roadblocks for

6 Microarray gene expression models: statistical perspectives

7 Asymptotics under null and local alternatives

8 Applications of Hamming distance measures

9 Discussion


Asymptotic Expansions of the Distributions of the Least Squares Estimators in Factor Analysis and Structural Equation Modeling

1 Introduction

2 Least squares estimators for unstandardized variables

3 Asymptotic distributions of the least squares estimators

4 Least squares estimators for standardized variables

5 Numerical examples

6 Discussion


Appendix A The partial derivatives of the parameter estimators with respect to sample variances and covariances

Multiple Testing of Hypotheses in Biomedical Research

1 Introduction

2 What is multiple testing?

3 Parametric approach

4 Nonparametric procedure

5 The enigma of p-values

6 Analogues of Type I error rates

7 Multiple testing procedures

8 Conclusions

Applications of Bayesian Neural Networks in Prostate Cancer Study

1 Introduction

2 Feedforward neural networks: frequentist and Bayesian approach

3 Priors and their properties

4 Prostate cancer: univariate analysis with clinical covariates

5 Multivariate analysis with clinical covariates

6 Univariate and multivariate analysis with gene expression data

7 Summary and conclusion

Statistical Methods for Detecting Functional Divergence of Gene Families

1 Introduction

2 The two-state model for functional divergence

3 Testing type-I functional divergence after gene duplication

4 Predicting critical residues for (type-I) functional divergence

5 Implementation and case-study

Sequence Pattern Discovery with Applications to Understanding Gene Regulation and Vaccine Design

1 Introduction

2 Pattern discovery in studying gene regulation

3 Hidden Markov models for sequence analysis

4 Using auxiliary data in motif prediction

5 Vaccine development using a pattern discovery approach

6 Pattern discovery using amino acid properties

7 Using HMMs to classify binders and non-binders

8 Concluding remarks

Single-Locus Genetic Association Analysis by Ordinal Tests

1 Introduction

2 Penetrance model for single-locus genetic association

3 Indirect association and two-locus model

4 Single-locus association tests

5 Statistical methods for ordered categorical data analysis

6 The equivalence between the CML test and the Bartholomew’s Chibar test

7 Type I error of different single-locus association tests

8 Power of different single-locus association tests

9 Simulation study using real HapMap ENCODE data

10 Conclusion

A Molecular Information Method to Estimate Populat on Admixture

1 Introduction

2 Materials and methods

3 Results

4 Discussion

Effects of Inclusion of Relatives in DNA Databases: Empirical Observations from 13K SNPs in Hap-Map Population Data

1 Introduction

2 Material and methods

3 Results

4 Discussion

Measurement and Analysis of Quality of Life in Epidemiology

1 Introduction

2 Measurement models of Health related Quality of Life

3 Validation of HrQoL measurement models

4 Construction of Quality of Life scores

5 Analysis of Quality of Life change between groups

6 Simulation results

7 Real data examples

8 Conclusion

Annex: A SAS Macro for the -curve

Quality of Life Perspectives in Chronic Disease and Disorder Studies

1 Introduction

2 Biology of diabetes

3 Genetics of Thalassemia minor

4 Nondegradation vs. degradation processes

5 QAL survival analysis

6 QAS analysis in diabetes studies—QOL aspects

7 Need for data collection, monitoring, and analysis

8 Some simulation studies

Bioinformatics of Obesity

1 Introduction

2 Epistemology and history of obesity

3 Measurements and types of obesity

4 Relationships between various measures of obesity and their implications

5 Diseases associated with obesity

6 Causes of obesity

7 Combating obesity epidemics

8 Future studies and epilogue

Exploring Genetic Epidemiology Data with Bayesian Networks

1 Introduction

2 Bayesian Networks

3 Example application in genetic epidemiology

4 Software and applications

5 Summary and future directions

Perturbation Methods for Protecting Numerical Data: Evolution and Evaluation

1 Introduction

2 Definition of data utility and disclosure risk for perturbation methods

3 The theoretical basis for perturbation methods

4 Evolution of perturbation methods for numerical data

5 Evaluation of perturbation methods

6 Comparison of perturbation with other masking methods

7 Conclusions

Protecting Data Confidentiality in Publicly Released Datasets: Approaches Based on Multiple Imputation

1 Introduction

2 Description of synthetic data methods

3 Inferential methods

4 Concluding remarks

Subject Index

Contents of Volumes


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.

Key Features

  • 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


Statisticians and scientists in various disciplines who use statistical methodology in their work


No. of pages:
© North Holland 2012
30th August 2012
North Holland
Hardcover ISBN:
eBook ISBN:

Ratings and Reviews

About the Series Volume Editors

C.R. Rao

C.R. Rao

Professor 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.

Affiliations and Expertise

The Pennsylvania State University, University Park, PA, USA

Ranajit Chakraborty

Affiliations and Expertise

Director, Center for Computational Genomics Institute of Applied Genetics Professor, Department of Forensic and Investigative Genetics University of North Texas Health Science Center 3500 Camp Bowie Blvd., Fort Worth, Texas 76107

Pranab Sen

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.

Affiliations and Expertise

University of North Carolina, Chapel Hill, U.S.A.