生物統(tǒng)計(jì)學(xué)和生物信息學(xué)最新進(jìn)展

Preface
Part Ⅰ Analysis of Survival and Longitudinal Data
Chapter 1 Non- and Semi- Parametric Modeling in Survival Analysis
1 Introduction
2 Cox's type of models
3 Multivariate Cox's type of models
4 Model selection on Cox's models
5 Validating Cox's type of models
6 Transformation models
7 Concluding remarks
References
Chapter 2 Additive-Accelerated Rate Model for Recurrent Event
1 Introduction
2 Inference procedure and asymptotic properties
3 Assessing additive and accelerated covariates
4 Simulation studies
5 Application
6 Remarks
Acknowledgements
Appendix
References
Chapter 3 An Overview on Quadratic Inference Function Approaches for Longitudinal Data
1 Introduction
2 The quadratic inference function approach
3 Penalized quadratic inference function
4 Some applications of QIF
5 Further research and concluding remarks
Acknowledgements
References
Chapter 4 Modeling and Analysis of Spatially Correlated Data
1 Introduction
2 Basic concepts of spatial process
3 Spatial models for non-normal/discrete data
4 Spatial models for censored outcome data
5 Concluding remarks
References
Part Ⅱ Statistical Methods for Epidemiology
Chapter 5 Study Designs for Biomarker-Based Treatment Selection
1 Introduction
2 Definition of study designs
3 Test of hypotheses and sample size calculation
4 Sample size calculation
5 Numerical comparisons of efficiency
6 Conclusions
Acknowledgements
Appendix
References
Chapter 6 Statistical Methods for Analyzing Two-Phase Studies
1 Introduction
2 Two-phase case-control or cross-sectional studies
3 Two-phase designs in cohort studies
4 Conclusions
References
Part Ⅲ Bioinformatics
Chapter 7 Protein Interaction Predictions from Diverse Sources
1 Introduction
2 Data sources useful for protein interaction predictions
3 Domain-based methods
4 Classification methods
5 Complex detection methods
6 Conclusions
Acknowledgements
References
Chapter 8 Regulatory Motif Discovery" From Decoding to Meta-Analysis
1 Introduction
2 A Bayesian approach to motif discovery
3 Discovery of regulatory modules
4 Motif discovery in multiple species
5 Motif learning on ChiP-chip data
6 Using nucleosome positioning information in motif discovery
7 Conclusion
References
Chapter 9 Analysis of Cancer Genome Alterations Using Singk Nucleotide Polymorphism (SNP) Microarrays
1 Background
2 Loss of heterozygosity analysis using SNP arrays
3 Copy number analysis using SNP arrays
4 High-level analysis using LOH and copy number data
5 Software for cancer alteration analysis using SNP arrays
6 Prospects
Acknowledgements
References
Chapter 10 Analysis of ChiP-chip Data on Genome Tiling Microarrays
1 Background molecular biology
2 A ChiP-chip experiment
3 Data description and analysis
4 Follow-up analysis
5 Conclusion
References
Subject Index
Author Index