生物统计及生物信息学前沿

作为现代科学的一个重要分支，生物统计和生物信息学运用统计、数学和计算机科学的方法研究生物及医学问题。在本书中，收录了15篇文章介绍生物统计和生物信息学中统计方法的最新进展。由于篇幅有限，着重介绍了高维数据分析方法及其应用。和统计学的其他分支相比，高维数据分析方法及其应用还处在相对初级阶段，希望本书的出版能够推动此方向的研究。

Preface to the USTC Alumni's Series From the Editors Shuangge Ma & Yuedong Wang Preface Shaw-Hwa Lo Section Ⅰ Statistical Genetics Linkage Analysis with Mixed Sample of Affected Full and Half Sib Pairs in the Presence of Uncertain Relationship Sequential Importance Sampling with Resampling in Molecular Population Genetics Multiple-trait Quantitative Trait Loci Mapping Using Stochastic Search Variable Selection Section Ⅱ Statistical Analysis of Microarray Data Statistical Analysis of Microarray Time Course Gene Expression Data with Functional Hierarchical Models A Nonparametric Method for the Conservative Estimation of the Proportion of True Null Hypotheses Partial Consistent Normalization Methods of Microarray Data Variance Estimation for Gene-expression Microarray Data Section Ⅲ Computational Biology A Study of Protein Subcellular Localization Prediction Computational Methods for Biomolecular Sequence Comparison Statistical Learning on a Complex Metabolomic Dataset A Flexible Statistical Model for Chromatin Sequences Section Ⅳ General Methodology Some Advances in Finite Mixture Models Smoothing Spline ANOVA with Heterogeneous Variances and Application to Kernel Estimation in Longitudinal Data with Outcome-related Observation Times A Computable Bound for the Geometric Convergence Rate of the Lasso Gibbs Sampler Brief Introduction of Authors