Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field (Hardcover, 2020)

Preface.- Part I: Next Generation Sequence Data Analysis.- 1. Modeling Species Specific Gene Expression Across Multiple Regions in the Brain.- 2. Classification of EEG Motion Artifact Signals Using Spatial ICA.- 3. Weighted K-means Clustering with Observation Weight for Single-cell Epigenomic Data.- 4. Discrete Multiple Testing in Detecting Differential Methylation Using Sequencing Data.- Part II: Deep Learning, Precision Medicine and Applications.- 5. Prediction of Functional Markers of Mass Cytometry Data via Deep Learning.- 6. Building Health Application Recommender System Using Partially Penalized Regression.- 7. Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data.- Part III: Large  Scale  Data Analysis and its Applications.- 8. Privacy Preserving Feature Selection Via Voted Wrapper Method For Horizontally Distributed Medical Data.- 9.  Improving Maize Trait through Modifying Combination of Genes.- 10.  Molecular Basis of Food Classification in Traditional Chinese Medicine.- 11. Discovery Among Binary Biomarkers in Heterogeneous Populations.- Part IV:  Biomedical Research and the Modelling.- 12.  Heat Kernel Smoothing on Manifolds and Its Application to Hyoid Bone Growth Modeling.- 13. Optimal Projections in the Distance-Based Statistical Methods.- 14. Kernel Tests for One, Two, and K-Sample Goodness-Of-Fit: State of the Art and Implementation Considerations.- 15. Hierarchical Modeling of the Effect of Pre-exposure Prophylaxis on HIV in the US.- 16. Mathematical Model of Mouse Ventricular Myocytes Overexpressing Adenylyl Cyclase Type 5.- Part V: Survival Analysis with Complex Data Structure and its Applications.- 17. Non-Parametric Maximum Likelihood Estimator for Case-Cohort and Nested Case-Control Designs with Competing Risks Data.- Authors:  Jie-Huei Wang, Chun-Hao Pan,  Yi-Hau Chen  and I-Shou Chang.- 18.  Variable Selection in Partially Linear Proportional Hazards  Model with Grouped Covariates and a Diverging Number of Parameters.- 19. Inference of Transition Probabilities in Multi-state Models using Adaptive Inverse Probability Censoring Weighting Technique.